--- _id: '5945' abstract: - lang: eng text: In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy. article_processing_charge: No article_type: original author: - first_name: Mariela D. full_name: Petkova, Mariela D. last_name: Petkova - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: William full_name: Bialek, William last_name: Bialek - first_name: Eric F. full_name: Wieschaus, Eric F. last_name: Wieschaus - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor citation: ama: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. Optimal decoding of cellular identities in a genetic network. Cell. 2019;176(4):844-855.e15. doi:10.1016/j.cell.2019.01.007 apa: Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., & Gregor, T. (2019). Optimal decoding of cellular identities in a genetic network. Cell. Cell Press. https://doi.org/10.1016/j.cell.2019.01.007 chicago: Petkova, Mariela D., Gašper Tkačik, William Bialek, Eric F. Wieschaus, and Thomas Gregor. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell. Cell Press, 2019. https://doi.org/10.1016/j.cell.2019.01.007. ieee: M. D. Petkova, G. Tkačik, W. Bialek, E. F. Wieschaus, and T. Gregor, “Optimal decoding of cellular identities in a genetic network,” Cell, vol. 176, no. 4. Cell Press, p. 844–855.e15, 2019. ista: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. 2019. Optimal decoding of cellular identities in a genetic network. Cell. 176(4), 844–855.e15. mla: Petkova, Mariela D., et al. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell, vol. 176, no. 4, Cell Press, 2019, p. 844–855.e15, doi:10.1016/j.cell.2019.01.007. short: M.D. Petkova, G. Tkačik, W. Bialek, E.F. Wieschaus, T. Gregor, Cell 176 (2019) 844–855.e15. date_created: 2019-02-10T22:59:16Z date_published: 2019-02-07T00:00:00Z date_updated: 2023-08-24T14:42:47Z day: '07' department: - _id: GaTk doi: 10.1016/j.cell.2019.01.007 external_id: isi: - '000457969200015' pmid: - '30712870' intvolume: ' 176' isi: 1 issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1016/j.cell.2019.01.007 month: '02' oa: 1 oa_version: Published Version page: 844-855.e15 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Cell publication_status: published publisher: Cell Press quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/cells-find-their-identity-using-a-mathematically-optimal-strategy/ scopus_import: '1' status: public title: Optimal decoding of cellular identities in a genetic network type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 176 year: '2019' ... --- _id: '6049' abstract: - lang: eng text: 'In this article it is shown that large systems with many interacting units endowing multiple phases display self-oscillations in the presence of linear feedback between the control and order parameters, where an Andronov–Hopf bifurcation takes over the phase transition. This is simply illustrated through the mean field Landau theory whose feedback dynamics turn out to be described by the Van der Pol equation and it is then validated for the fully connected Ising model following heat bath dynamics. Despite its simplicity, this theory accounts potentially for a rich range of phenomena: here it is applied to describe in a stylized way (i) excess demand-price cycles due to strong herding in a simple agent-based market model; (ii) congestion waves in queuing networks triggered by user feedback to delays in overloaded conditions; and (iii) metabolic network oscillations resulting from cell growth control in a bistable phenotypic landscape.' article_number: '045002' article_processing_charge: Yes (in subscription journal) author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: 'De Martino D. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 2019;52(4). doi:10.1088/1751-8121/aaf2dd' apa: 'De Martino, D. (2019). Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. IOP Publishing. https://doi.org/10.1088/1751-8121/aaf2dd' chicago: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical. IOP Publishing, 2019. https://doi.org/10.1088/1751-8121/aaf2dd.' ieee: 'D. De Martino, “Feedback-induced self-oscillations in large interacting systems subjected to phase transitions,” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4. IOP Publishing, 2019.' ista: 'De Martino D. 2019. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 52(4), 045002.' mla: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4, 045002, IOP Publishing, 2019, doi:10.1088/1751-8121/aaf2dd.' short: 'D. De Martino, Journal of Physics A: Mathematical and Theoretical 52 (2019).' date_created: 2019-02-24T22:59:19Z date_published: 2019-01-07T00:00:00Z date_updated: 2023-08-24T14:49:23Z day: '07' ddc: - '570' department: - _id: GaTk doi: 10.1088/1751-8121/aaf2dd ec_funded: 1 external_id: isi: - '000455379500001' file: - access_level: open_access checksum: 1112304ad363a6d8afaeccece36473cf content_type: application/pdf creator: kschuh date_created: 2019-04-19T12:18:57Z date_updated: 2020-07-14T12:47:17Z file_id: '6344' file_name: 2019_IOP_DeMartino.pdf file_size: 1804557 relation: main_file file_date_updated: 2020-07-14T12:47:17Z has_accepted_license: '1' intvolume: ' 52' isi: 1 issue: '4' language: - iso: eng month: '01' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: 'Journal of Physics A: Mathematical and Theoretical' publication_status: published publisher: IOP Publishing quality_controlled: '1' scopus_import: '1' status: public title: Feedback-induced self-oscillations in large interacting systems subjected to phase transitions tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 52 year: '2019' ... --- _id: '6046' abstract: - lang: eng text: Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time‐lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate‐limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses. acknowledged_ssus: - _id: Bio article_number: e8470 article_processing_charge: No author: - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Mitosch K, Rieckh G, Bollenbach MT. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 2019;15(2). doi:10.15252/msb.20188470 apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2019). Temporal order and precision of complex stress responses in individual bacteria. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.20188470 chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology. Embo Press, 2019. https://doi.org/10.15252/msb.20188470. ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Temporal order and precision of complex stress responses in individual bacteria,” Molecular systems biology, vol. 15, no. 2. Embo Press, 2019. ista: Mitosch K, Rieckh G, Bollenbach MT. 2019. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 15(2), e8470. mla: Mitosch, Karin, et al. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology, vol. 15, no. 2, e8470, Embo Press, 2019, doi:10.15252/msb.20188470. short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Molecular Systems Biology 15 (2019). date_created: 2019-02-24T22:59:18Z date_published: 2019-02-14T00:00:00Z date_updated: 2023-08-24T14:49:53Z day: '14' department: - _id: GaTk doi: 10.15252/msb.20188470 external_id: isi: - '000459628300003' pmid: - '30765425' intvolume: ' 15' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pubmed/30765425 month: '02' oa: 1 oa_version: Submitted Version pmid: 1 project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Molecular systems biology publication_status: published publisher: Embo Press quality_controlled: '1' scopus_import: '1' status: public title: Temporal order and precision of complex stress responses in individual bacteria type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '6784' abstract: - lang: eng text: Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their population size, with the first strategy favoring simple immunity featuring a single restriction modification system and the second strategy favoring complex bacterial innate immunity featuring several simultaneously active restriction modification systems. article_number: e1007168 article_processing_charge: No article_type: original author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Ruess J, Pleska M, Guet CC, Tkačik G. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 2019;15(7). doi:10.1371/journal.pcbi.1007168 apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168 chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168. ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Molecular noise of innate immunity shapes bacteria-phage ecologies,” PLoS Computational Biology, vol. 15, no. 7. Public Library of Science, 2019. ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 15(7), e1007168. mla: Ruess, Jakob, et al. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology, vol. 15, no. 7, e1007168, Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168. short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, PLoS Computational Biology 15 (2019). date_created: 2019-08-11T21:59:19Z date_published: 2019-07-02T00:00:00Z date_updated: 2023-08-29T07:10:06Z day: '02' ddc: - '570' department: - _id: CaGu - _id: GaTk doi: 10.1371/journal.pcbi.1007168 external_id: isi: - '000481577700032' file: - access_level: open_access checksum: 7ded4721b41c2a0fc66a1c634540416a content_type: application/pdf creator: dernst date_created: 2019-08-12T12:27:26Z date_updated: 2020-07-14T12:47:40Z file_id: '6803' file_name: 2019_PlosComputBiology_Ruess.pdf file_size: 2200003 relation: main_file file_date_updated: 2020-07-14T12:47:40Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '7' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 251D65D8-B435-11E9-9278-68D0E5697425 grant_number: '24210' name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level - _id: 251BCBEC-B435-11E9-9278-68D0E5697425 grant_number: RGY0079/2011 name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems publication: PLoS Computational Biology publication_identifier: eissn: - 1553-7358 publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: record: - id: '9786' relation: research_data status: public scopus_import: '1' status: public title: Molecular noise of innate immunity shapes bacteria-phage ecologies tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '9786' article_processing_charge: No author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Ruess J, Pleska M, Guet CC, Tkačik G. Supporting text and results. 2019. doi:10.1371/journal.pcbi.1007168.s001 apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Supporting text and results. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168.s001 chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Supporting Text and Results.” Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168.s001. ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Supporting text and results.” Public Library of Science, 2019. ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Supporting text and results, Public Library of Science, 10.1371/journal.pcbi.1007168.s001. mla: Ruess, Jakob, et al. Supporting Text and Results. Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168.s001. short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, (2019). date_created: 2021-08-06T08:23:43Z date_published: 2019-07-02T00:00:00Z date_updated: 2023-08-29T07:10:05Z day: '02' department: - _id: CaGu - _id: GaTk doi: 10.1371/journal.pcbi.1007168.s001 month: '07' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '6784' relation: used_in_publication status: public status: public title: Supporting text and results type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2019' ... --- _id: '7422' abstract: - lang: eng text: Biochemical reactions often occur at low copy numbers but at once in crowded and diverse environments. Space and stochasticity therefore play an essential role in biochemical networks. Spatial-stochastic simulations have become a prominent tool for understanding how stochasticity at the microscopic level influences the macroscopic behavior of such systems. While particle-based models guarantee the level of detail necessary to accurately describe the microscopic dynamics at very low copy numbers, the algorithms used to simulate them typically imply trade-offs between computational efficiency and biochemical accuracy. eGFRD (enhanced Green’s Function Reaction Dynamics) is an exact algorithm that evades such trade-offs by partitioning the N-particle system into M ≤ N analytically tractable one- and two-particle systems; the analytical solutions (Green’s functions) then are used to implement an event-driven particle-based scheme that allows particles to make large jumps in time and space while retaining access to their state variables at arbitrary simulation times. Here we present “eGFRD2,” a new eGFRD version that implements the principle of eGFRD in all dimensions, thus enabling efficient particle-based simulation of biochemical reaction-diffusion processes in the 3D cytoplasm, on 2D planes representing membranes, and on 1D elongated cylinders representative of, e.g., cytoskeletal tracks or DNA; in 1D, it also incorporates convective motion used to model active transport. We find that, for low particle densities, eGFRD2 is up to 6 orders of magnitude faster than conventional Brownian dynamics. We exemplify the capabilities of eGFRD2 by simulating an idealized model of Pom1 gradient formation, which involves 3D diffusion, active transport on microtubules, and autophosphorylation on the membrane, confirming recent experimental and theoretical results on this system to hold under genuinely stochastic conditions. article_number: '054108' article_processing_charge: No article_type: original author: - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Joris full_name: Paijmans, Joris last_name: Paijmans - first_name: Laurens full_name: Bossen, Laurens last_name: Bossen - first_name: Thomas full_name: Miedema, Thomas last_name: Miedema - first_name: Martijn full_name: Wehrens, Martijn last_name: Wehrens - first_name: Nils B. full_name: Becker, Nils B. last_name: Becker - first_name: Kazunari full_name: Kaizu, Kazunari last_name: Kaizu - first_name: Koichi full_name: Takahashi, Koichi last_name: Takahashi - first_name: Marileen full_name: Dogterom, Marileen last_name: Dogterom - first_name: Pieter Rein full_name: ten Wolde, Pieter Rein last_name: ten Wolde citation: ama: Sokolowski TR, Paijmans J, Bossen L, et al. eGFRD in all dimensions. The Journal of Chemical Physics. 2019;150(5). doi:10.1063/1.5064867 apa: Sokolowski, T. R., Paijmans, J., Bossen, L., Miedema, T., Wehrens, M., Becker, N. B., … ten Wolde, P. R. (2019). eGFRD in all dimensions. The Journal of Chemical Physics. AIP Publishing. https://doi.org/10.1063/1.5064867 chicago: Sokolowski, Thomas R, Joris Paijmans, Laurens Bossen, Thomas Miedema, Martijn Wehrens, Nils B. Becker, Kazunari Kaizu, Koichi Takahashi, Marileen Dogterom, and Pieter Rein ten Wolde. “EGFRD in All Dimensions.” The Journal of Chemical Physics. AIP Publishing, 2019. https://doi.org/10.1063/1.5064867. ieee: T. R. Sokolowski et al., “eGFRD in all dimensions,” The Journal of Chemical Physics, vol. 150, no. 5. AIP Publishing, 2019. ista: Sokolowski TR, Paijmans J, Bossen L, Miedema T, Wehrens M, Becker NB, Kaizu K, Takahashi K, Dogterom M, ten Wolde PR. 2019. eGFRD in all dimensions. The Journal of Chemical Physics. 150(5), 054108. mla: Sokolowski, Thomas R., et al. “EGFRD in All Dimensions.” The Journal of Chemical Physics, vol. 150, no. 5, 054108, AIP Publishing, 2019, doi:10.1063/1.5064867. short: T.R. Sokolowski, J. Paijmans, L. Bossen, T. Miedema, M. Wehrens, N.B. Becker, K. Kaizu, K. Takahashi, M. Dogterom, P.R. ten Wolde, The Journal of Chemical Physics 150 (2019). date_created: 2020-01-30T10:34:36Z date_published: 2019-02-07T00:00:00Z date_updated: 2023-09-06T14:59:28Z day: '07' department: - _id: GaTk doi: 10.1063/1.5064867 external_id: arxiv: - '1708.09364' isi: - '000458109300009' intvolume: ' 150' isi: 1 issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1708.09364 month: '02' oa: 1 oa_version: Preprint publication: The Journal of Chemical Physics publication_identifier: eissn: - 1089-7690 issn: - 0021-9606 publication_status: published publisher: AIP Publishing quality_controlled: '1' status: public title: eGFRD in all dimensions type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 150 year: '2019' ... --- _id: '6900' abstract: - lang: eng text: Across diverse biological systems—ranging from neural networks to intracellular signaling and genetic regulatory networks—the information about changes in the environment is frequently encoded in the full temporal dynamics of the network nodes. A pressing data-analysis challenge has thus been to efficiently estimate the amount of information that these dynamics convey from experimental data. Here we develop and evaluate decoding-based estimation methods to lower bound the mutual information about a finite set of inputs, encoded in single-cell high-dimensional time series data. For biological reaction networks governed by the chemical Master equation, we derive model-based information approximations and analytical upper bounds, against which we benchmark our proposed model-free decoding estimators. In contrast to the frequently-used k-nearest-neighbor estimator, decoding-based estimators robustly extract a large fraction of the available information from high-dimensional trajectories with a realistic number of data samples. We apply these estimators to previously published data on Erk and Ca2+ signaling in mammalian cells and to yeast stress-response, and find that substantial amount of information about environmental state can be encoded by non-trivial response statistics even in stationary signals. We argue that these single-cell, decoding-based information estimates, rather than the commonly-used tests for significant differences between selected population response statistics, provide a proper and unbiased measure for the performance of biological signaling networks. article_processing_charge: No author: - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Jakob full_name: Ruess, Jakob last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Cepeda Humerez SA, Ruess J, Tkačik G. Estimating information in time-varying signals. PLoS computational biology. 2019;15(9):e1007290. doi:10.1371/journal.pcbi.1007290 apa: Cepeda Humerez, S. A., Ruess, J., & Tkačik, G. (2019). Estimating information in time-varying signals. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007290 chicago: Cepeda Humerez, Sarah A, Jakob Ruess, and Gašper Tkačik. “Estimating Information in Time-Varying Signals.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007290. ieee: S. A. Cepeda Humerez, J. Ruess, and G. Tkačik, “Estimating information in time-varying signals,” PLoS computational biology, vol. 15, no. 9. Public Library of Science, p. e1007290, 2019. ista: Cepeda Humerez SA, Ruess J, Tkačik G. 2019. Estimating information in time-varying signals. PLoS computational biology. 15(9), e1007290. mla: Cepeda Humerez, Sarah A., et al. “Estimating Information in Time-Varying Signals.” PLoS Computational Biology, vol. 15, no. 9, Public Library of Science, 2019, p. e1007290, doi:10.1371/journal.pcbi.1007290. short: S.A. Cepeda Humerez, J. Ruess, G. Tkačik, PLoS Computational Biology 15 (2019) e1007290. date_created: 2019-09-22T22:00:37Z date_published: 2019-09-03T00:00:00Z date_updated: 2023-09-07T12:55:21Z day: '03' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1007290 external_id: isi: - '000489741800021' pmid: - '31479447' file: - access_level: open_access checksum: 81bdce1361c9aa8395d6fa635fb6ab47 content_type: application/pdf creator: kschuh date_created: 2019-10-01T10:53:45Z date_updated: 2020-07-14T12:47:44Z file_id: '6925' file_name: 2019_PLoS_Cepeda-Humerez.pdf file_size: 3081855 relation: main_file file_date_updated: 2020-07-14T12:47:44Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '9' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: e1007290 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: PLoS computational biology publication_identifier: eissn: - '15537358' publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: '1' status: public title: Estimating information in time-varying signals tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '196' abstract: - lang: eng text: 'The abelian sandpile serves as a model to study self-organized criticality, a phenomenon occurring in biological, physical and social processes. The identity of the abelian group is a fractal composed of self-similar patches, and its limit is subject of extensive collaborative research. Here, we analyze the evolution of the sandpile identity under harmonic fields of different orders. We show that this evolution corresponds to periodic cycles through the abelian group characterized by the smooth transformation and apparent conservation of the patches constituting the identity. The dynamics induced by second and third order harmonics resemble smooth stretchings, respectively translations, of the identity, while the ones induced by fourth order harmonics resemble magnifications and rotations. Starting with order three, the dynamics pass through extended regions of seemingly random configurations which spontaneously reassemble into accentuated patterns. We show that the space of harmonic functions projects to the extended analogue of the sandpile group, thus providing a set of universal coordinates identifying configurations between different domains. Since the original sandpile group is a subgroup of the extended one, this directly implies that it admits a natural renormalization. Furthermore, we show that the harmonic fields can be induced by simple Markov processes, and that the corresponding stochastic dynamics show remarkable robustness over hundreds of periods. Finally, we encode information into seemingly random configurations, and decode this information with an algorithm requiring minimal prior knowledge. Our results suggest that harmonic fields might split the sandpile group into sub-sets showing different critical coefficients, and that it might be possible to extend the fractal structure of the identity beyond the boundaries of its domain. ' acknowledgement: "M.L. is grateful to the members of the C Guet and G Tkacik groups for valuable comments and support. M.S. is grateful to Nikita Kalinin for inspiring communications.\r\n" article_processing_charge: No article_type: original author: - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Mikhail full_name: Shkolnikov, Mikhail id: 35084A62-F248-11E8-B48F-1D18A9856A87 last_name: Shkolnikov orcid: 0000-0002-4310-178X citation: ama: Lang M, Shkolnikov M. Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. 2019;116(8):2821-2830. doi:10.1073/pnas.1812015116 apa: Lang, M., & Shkolnikov, M. (2019). Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. National Academy of Sciences. https://doi.org/10.1073/pnas.1812015116 chicago: Lang, Moritz, and Mikhail Shkolnikov. “Harmonic Dynamics of the Abelian Sandpile.” Proceedings of the National Academy of Sciences. National Academy of Sciences, 2019. https://doi.org/10.1073/pnas.1812015116. ieee: M. Lang and M. Shkolnikov, “Harmonic dynamics of the Abelian sandpile,” Proceedings of the National Academy of Sciences, vol. 116, no. 8. National Academy of Sciences, pp. 2821–2830, 2019. ista: Lang M, Shkolnikov M. 2019. Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. 116(8), 2821–2830. mla: Lang, Moritz, and Mikhail Shkolnikov. “Harmonic Dynamics of the Abelian Sandpile.” Proceedings of the National Academy of Sciences, vol. 116, no. 8, National Academy of Sciences, 2019, pp. 2821–30, doi:10.1073/pnas.1812015116. short: M. Lang, M. Shkolnikov, Proceedings of the National Academy of Sciences 116 (2019) 2821–2830. date_created: 2018-12-11T11:45:08Z date_published: 2019-02-19T00:00:00Z date_updated: 2023-09-11T14:09:34Z day: '19' department: - _id: CaGu - _id: GaTk - _id: TaHa doi: 10.1073/pnas.1812015116 external_id: arxiv: - '1806.10823' isi: - '000459074400013' pmid: - ' 30728300' intvolume: ' 116' isi: 1 issue: '8' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1073/pnas.1812015116 month: '02' oa: 1 oa_version: Published Version page: 2821-2830 pmid: 1 publication: Proceedings of the National Academy of Sciences publication_identifier: eissn: - 1091-6490 publication_status: published publisher: National Academy of Sciences quality_controlled: '1' related_material: link: - description: News on IST Webpage relation: press_release url: https://ist.ac.at/en/news/famous-sandpile-model-shown-to-move-like-a-traveling-sand-dune/ scopus_import: '1' status: public title: Harmonic dynamics of the Abelian sandpile type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 116 year: '2019' ... --- _id: '5817' abstract: - lang: eng text: We theoretically study the shapes of lipid vesicles confined to a spherical cavity, elaborating a framework based on the so-called limiting shapes constructed from geometrically simple structural elements such as double-membrane walls and edges. Partly inspired by numerical results, the proposed non-compartmentalized and compartmentalized limiting shapes are arranged in the bilayer-couple phase diagram which is then compared to its free-vesicle counterpart. We also compute the area-difference-elasticity phase diagram of the limiting shapes and we use it to interpret shape transitions experimentally observed in vesicles confined within another vesicle. The limiting-shape framework may be generalized to theoretically investigate the structure of certain cell organelles such as the mitochondrion. article_processing_charge: No article_type: original author: - first_name: Bor full_name: Kavcic, Bor id: 350F91D2-F248-11E8-B48F-1D18A9856A87 last_name: Kavcic orcid: 0000-0001-6041-254X - first_name: A. full_name: Sakashita, A. last_name: Sakashita - first_name: H. full_name: Noguchi, H. last_name: Noguchi - first_name: P. full_name: Ziherl, P. last_name: Ziherl citation: ama: Kavcic B, Sakashita A, Noguchi H, Ziherl P. Limiting shapes of confined lipid vesicles. Soft Matter. 2019;15(4):602-614. doi:10.1039/c8sm01956h apa: Kavcic, B., Sakashita, A., Noguchi, H., & Ziherl, P. (2019). Limiting shapes of confined lipid vesicles. Soft Matter. Royal Society of Chemistry. https://doi.org/10.1039/c8sm01956h chicago: Kavcic, Bor, A. Sakashita, H. Noguchi, and P. Ziherl. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter. Royal Society of Chemistry, 2019. https://doi.org/10.1039/c8sm01956h. ieee: B. Kavcic, A. Sakashita, H. Noguchi, and P. Ziherl, “Limiting shapes of confined lipid vesicles,” Soft Matter, vol. 15, no. 4. Royal Society of Chemistry, pp. 602–614, 2019. ista: Kavcic B, Sakashita A, Noguchi H, Ziherl P. 2019. Limiting shapes of confined lipid vesicles. Soft Matter. 15(4), 602–614. mla: Kavcic, Bor, et al. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter, vol. 15, no. 4, Royal Society of Chemistry, 2019, pp. 602–14, doi:10.1039/c8sm01956h. short: B. Kavcic, A. Sakashita, H. Noguchi, P. Ziherl, Soft Matter 15 (2019) 602–614. date_created: 2019-01-11T07:37:47Z date_published: 2019-01-10T00:00:00Z date_updated: 2023-09-13T08:47:16Z day: '10' ddc: - '530' department: - _id: GaTk doi: 10.1039/c8sm01956h external_id: isi: - '000457329700003' pmid: - '30629082' file: - access_level: open_access checksum: 614c337d6424ccd3d48d1b1f9513510d content_type: application/pdf creator: bkavcic date_created: 2020-10-09T11:00:05Z date_updated: 2020-10-09T11:00:05Z file_id: '8641' file_name: lmt_sftmtr_V8.pdf file_size: 5370762 relation: main_file success: 1 file_date_updated: 2020-10-09T11:00:05Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '4' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/3.0/ month: '01' oa: 1 oa_version: Submitted Version page: 602-614 pmid: 1 publication: Soft Matter publication_identifier: eissn: - 1744-6848 issn: - 1744-683X publication_status: published publisher: Royal Society of Chemistry quality_controlled: '1' scopus_import: '1' status: public title: Limiting shapes of confined lipid vesicles tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 15 year: '2019' ... --- _id: '6473' abstract: - lang: eng text: "Single cells are constantly interacting with their environment and each other, more importantly, the accurate perception of environmental cues is crucial for growth, survival, and reproduction. This communication between cells and their environment can be formalized in mathematical terms and be quantified as the information flow between them, as prescribed by information theory. \r\nThe recent availability of real–time dynamical patterns of signaling molecules in single cells has allowed us to identify encoding about the identity of the environment in the time–series. However, efficient estimation of the information transmitted by these signals has been a data–analysis challenge due to the high dimensionality of the trajectories and the limited number of samples. In the first part of this thesis, we develop and evaluate decoding–based estimation methods to lower bound the mutual information and derive model–based precise information estimates for biological reaction networks governed by the chemical master equation. This is followed by applying the decoding-based methods to study the intracellular representation of extracellular changes in budding yeast, by observing the transient dynamics of nuclear translocation of 10 transcription factors in response to 3 stress conditions. Additionally, we apply these estimators to previously published data on ERK and Ca2+ signaling and yeast stress response. We argue that this single cell decoding-based measure of information provides an unbiased, quantitative and interpretable measure for the fidelity of biological signaling processes. \r\nFinally, in the last section, we deal with gene regulation which is primarily controlled by transcription factors (TFs) that bind to the DNA to activate gene expression. The possibility that non-cognate TFs activate transcription diminishes the accuracy of regulation with potentially disastrous effects for the cell. This ’crosstalk’ acts as a previously unexplored source of noise in biochemical networks and puts a strong constraint on their performance. To mitigate erroneous initiation we propose an out of equilibrium scheme that implements kinetic proofreading. We show that such architectures are favored over their equilibrium counterparts for complex organisms despite introducing noise in gene expression. " alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez citation: ama: Cepeda Humerez SA. Estimating information flow in single cells. 2019. doi:10.15479/AT:ISTA:6473 apa: Cepeda Humerez, S. A. (2019). Estimating information flow in single cells. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:6473 chicago: Cepeda Humerez, Sarah A. “Estimating Information Flow in Single Cells.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/AT:ISTA:6473. ieee: S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute of Science and Technology Austria, 2019. ista: Cepeda Humerez SA. 2019. Estimating information flow in single cells. Institute of Science and Technology Austria. mla: Cepeda Humerez, Sarah A. Estimating Information Flow in Single Cells. Institute of Science and Technology Austria, 2019, doi:10.15479/AT:ISTA:6473. short: S.A. Cepeda Humerez, Estimating Information Flow in Single Cells, Institute of Science and Technology Austria, 2019. date_created: 2019-05-21T00:11:23Z date_published: 2019-05-23T00:00:00Z date_updated: 2023-09-19T15:13:26Z day: '23' ddc: - '004' degree_awarded: PhD department: - _id: GaTk doi: 10.15479/AT:ISTA:6473 file: - access_level: closed checksum: 75f9184c1346e10a5de5f9cc7338309a content_type: application/zip creator: scepeda date_created: 2019-05-23T11:18:16Z date_updated: 2020-07-14T12:47:31Z file_id: '6480' file_name: Thesis_Cepeda.zip file_size: 23937464 relation: source_file - access_level: open_access checksum: afdc0633ddbd71d5b13550d7fb4f4454 content_type: application/pdf creator: scepeda date_created: 2019-05-23T11:18:13Z date_updated: 2020-07-14T12:47:31Z file_id: '6481' file_name: CepedaThesis.pdf file_size: 16646985 relation: main_file file_date_updated: 2020-07-14T12:47:31Z has_accepted_license: '1' keyword: - Information estimation - Time-series - data analysis language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '135' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '1576' relation: dissertation_contains status: public - id: '6900' relation: dissertation_contains status: public - id: '281' relation: dissertation_contains status: public - id: '2016' relation: dissertation_contains status: public status: public supervisor: - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 title: Estimating information flow in single cells tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ... --- _id: '6071' abstract: - lang: eng text: 'Transcription factors, by binding to specific sequences on the DNA, control the precise spatio-temporal expression of genes inside a cell. However, this specificity is limited, leading to frequent incorrect binding of transcription factors that might have deleterious consequences on the cell. By constructing a biophysical model of TF-DNA binding in the context of gene regulation, I will first explore how regulatory constraints can strongly shape the distribution of a population in sequence space. Then, by directly linking this to a picture of multiple types of transcription factors performing their functions simultaneously inside the cell, I will explore the extent of regulatory crosstalk -- incorrect binding interactions between transcription factors and binding sites that lead to erroneous regulatory states -- and understand the constraints this places on the design of regulatory systems. I will then develop a generic theoretical framework to investigate the coevolution of multiple transcription factors and multiple binding sites, in the context of a gene regulatory network that performs a certain function. As a particular tractable version of this problem, I will consider the evolution of two transcription factors when they transmit upstream signals to downstream target genes. Specifically, I will describe the evolutionary steady states and the evolutionary pathways involved, along with their timescales, of a system that initially undergoes a transcription factor duplication event. To connect this important theoretical model to the prominent biological event of transcription factor duplication giving rise to paralogous families, I will then describe a bioinformatics analysis of C2H2 Zn-finger transcription factors, a major family in humans, and focus on the patterns of evolution that paralogs have undergone in their various protein domains in the recent past. ' alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak citation: ama: Prizak R. Coevolution of transcription factors and their binding sites in sequence space. 2019. doi:10.15479/at:ista:th6071 apa: Prizak, R. (2019). Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:th6071 chicago: Prizak, Roshan. “Coevolution of Transcription Factors and Their Binding Sites in Sequence Space.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/at:ista:th6071. ieee: R. Prizak, “Coevolution of transcription factors and their binding sites in sequence space,” Institute of Science and Technology Austria, 2019. ista: Prizak R. 2019. Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria. mla: Prizak, Roshan. Coevolution of Transcription Factors and Their Binding Sites in Sequence Space. Institute of Science and Technology Austria, 2019, doi:10.15479/at:ista:th6071. short: R. Prizak, Coevolution of Transcription Factors and Their Binding Sites in Sequence Space, Institute of Science and Technology Austria, 2019. date_created: 2019-03-06T16:16:10Z date_published: 2019-03-11T00:00:00Z date_updated: 2023-09-22T10:00:48Z day: '11' ddc: - '576' degree_awarded: PhD department: - _id: GaTk - _id: NiBa doi: 10.15479/at:ista:th6071 file: - access_level: open_access checksum: e60a72de35d270b31f1a23d50f224ec0 content_type: application/pdf creator: rprizak date_created: 2019-03-06T16:05:07Z date_updated: 2020-07-14T12:47:18Z file_id: '6072' file_name: Thesis_final_PDFA_RoshanPrizak.pdf file_size: 20995465 relation: main_file - access_level: closed checksum: 67c2630333d05ebafef5f018863a8465 content_type: application/zip creator: rprizak date_created: 2019-03-06T16:09:39Z date_updated: 2020-07-14T12:47:18Z file_id: '6073' file_name: thesis_v2_merge.zip file_size: 85705272 relation: source_file title: Latex files file_date_updated: 2020-07-14T12:47:18Z has_accepted_license: '1' language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: '189' project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '1358' relation: part_of_dissertation status: public - id: '955' relation: part_of_dissertation status: public status: public supervisor: - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 title: Coevolution of transcription factors and their binding sites in sequence space type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ... --- _id: '7103' abstract: - lang: eng text: Origin and functions of intermittent transitions among sleep stages, including short awakenings and arousals, constitute a challenge to the current homeostatic framework for sleep regulation, focusing on factors modulating sleep over large time scales. Here we propose that the complex micro-architecture characterizing the sleep-wake cycle results from an underlying non-equilibrium critical dynamics, bridging collective behaviors across spatio-temporal scales. We investigate θ and δ wave dynamics in control rats and in rats with lesions of sleep-promoting neurons in the parafacial zone. We demonstrate that intermittent bursts in θ and δ rhythms exhibit a complex temporal organization, with long-range power-law correlations and a robust duality of power law (θ-bursts, active phase) and exponential-like (δ-bursts, quiescent phase) duration distributions, typical features of non-equilibrium systems self-organizing at criticality. Crucially, such temporal organization relates to anti-correlated coupling between θ- and δ-bursts, and is independent of the dominant physiologic state and lesions, a solid indication of a basic principle in sleep dynamics. article_number: e1007268 article_processing_charge: No article_type: original author: - first_name: Jilin W. J. L. full_name: Wang, Jilin W. J. L. last_name: Wang - first_name: Fabrizio full_name: Lombardi, Fabrizio id: A057D288-3E88-11E9-986D-0CF4E5697425 last_name: Lombardi orcid: 0000-0003-2623-5249 - first_name: Xiyun full_name: Zhang, Xiyun last_name: Zhang - first_name: Christelle full_name: Anaclet, Christelle last_name: Anaclet - first_name: Plamen Ch. full_name: Ivanov, Plamen Ch. last_name: Ivanov citation: ama: Wang JWJL, Lombardi F, Zhang X, Anaclet C, Ivanov PC. Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. 2019;15(11). doi:10.1371/journal.pcbi.1007268 apa: Wang, J. W. J. L., Lombardi, F., Zhang, X., Anaclet, C., & Ivanov, P. C. (2019). Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007268 chicago: Wang, Jilin W. J. L., Fabrizio Lombardi, Xiyun Zhang, Christelle Anaclet, and Plamen Ch. Ivanov. “Non-Equilibrium Critical Dynamics of Bursts in θ and δ Rhythms as Fundamental Characteristic of Sleep and Wake Micro-Architecture.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007268. ieee: J. W. J. L. Wang, F. Lombardi, X. Zhang, C. Anaclet, and P. C. Ivanov, “Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture,” PLoS Computational Biology, vol. 15, no. 11. Public Library of Science, 2019. ista: Wang JWJL, Lombardi F, Zhang X, Anaclet C, Ivanov PC. 2019. Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. 15(11), e1007268. mla: Wang, Jilin W. J. L., et al. “Non-Equilibrium Critical Dynamics of Bursts in θ and δ Rhythms as Fundamental Characteristic of Sleep and Wake Micro-Architecture.” PLoS Computational Biology, vol. 15, no. 11, e1007268, Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007268. short: J.W.J.L. Wang, F. Lombardi, X. Zhang, C. Anaclet, P.C. Ivanov, PLoS Computational Biology 15 (2019). date_created: 2019-11-25T08:20:47Z date_published: 2019-11-01T00:00:00Z date_updated: 2023-10-17T12:30:07Z day: '01' ddc: - '570' - '000' department: - _id: GaTk doi: 10.1371/journal.pcbi.1007268 ec_funded: 1 external_id: isi: - '000500976100014' pmid: - '31725712' file: - access_level: open_access checksum: 2a096a9c6dcc6eaa94077b2603bc6c12 content_type: application/pdf creator: dernst date_created: 2019-11-25T08:24:01Z date_updated: 2020-07-14T12:47:49Z file_id: '7104' file_name: 2019_PLOSComBio_Wang.pdf file_size: 3982516 relation: main_file file_date_updated: 2020-07-14T12:47:49Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '11' language: - iso: eng month: '11' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: PLoS Computational Biology publication_identifier: issn: - 1553-7358 publication_status: published publisher: Public Library of Science quality_controlled: '1' scopus_import: '1' status: public title: Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 15 year: '2019' ... --- _id: '6090' abstract: - lang: eng text: Cells need to reliably sense external ligand concentrations to achieve various biological functions such as chemotaxis or signaling. The molecular recognition of ligands by surface receptors is degenerate in many systems, leading to crosstalk between ligand-receptor pairs. Crosstalk is often thought of as a deviation from optimal specific recognition, as the binding of noncognate ligands can interfere with the detection of the receptor's cognate ligand, possibly leading to a false triggering of a downstream signaling pathway. Here we quantify the optimal precision of sensing the concentrations of multiple ligands by a collection of promiscuous receptors. We demonstrate that crosstalk can improve precision in concentration sensing and discrimination tasks. To achieve superior precision, the additional information about ligand concentrations contained in short binding events of the noncognate ligand should be exploited. We present a proofreading scheme to realize an approximate estimation of multiple ligand concentrations that reaches a precision close to the derived optimal bounds. Our results help rationalize the observed ubiquity of receptor crosstalk in molecular sensing. article_number: '022423' article_processing_charge: No author: - first_name: Martín full_name: Carballo-Pacheco, Martín last_name: Carballo-Pacheco - first_name: Jonathan full_name: Desponds, Jonathan last_name: Desponds - first_name: Tatyana full_name: Gavrilchenko, Tatyana last_name: Gavrilchenko - first_name: Andreas full_name: Mayer, Andreas last_name: Mayer - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Gautam full_name: Reddy, Gautam last_name: Reddy - first_name: Ilya full_name: Nemenman, Ilya last_name: Nemenman - first_name: Thierry full_name: Mora, Thierry last_name: Mora citation: ama: Carballo-Pacheco M, Desponds J, Gavrilchenko T, et al. Receptor crosstalk improves concentration sensing of multiple ligands. Physical Review E. 2019;99(2). doi:10.1103/PhysRevE.99.022423 apa: Carballo-Pacheco, M., Desponds, J., Gavrilchenko, T., Mayer, A., Prizak, R., Reddy, G., … Mora, T. (2019). Receptor crosstalk improves concentration sensing of multiple ligands. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.99.022423 chicago: Carballo-Pacheco, Martín, Jonathan Desponds, Tatyana Gavrilchenko, Andreas Mayer, Roshan Prizak, Gautam Reddy, Ilya Nemenman, and Thierry Mora. “Receptor Crosstalk Improves Concentration Sensing of Multiple Ligands.” Physical Review E. American Physical Society, 2019. https://doi.org/10.1103/PhysRevE.99.022423. ieee: M. Carballo-Pacheco et al., “Receptor crosstalk improves concentration sensing of multiple ligands,” Physical Review E, vol. 99, no. 2. American Physical Society, 2019. ista: Carballo-Pacheco M, Desponds J, Gavrilchenko T, Mayer A, Prizak R, Reddy G, Nemenman I, Mora T. 2019. Receptor crosstalk improves concentration sensing of multiple ligands. Physical Review E. 99(2), 022423. mla: Carballo-Pacheco, Martín, et al. “Receptor Crosstalk Improves Concentration Sensing of Multiple Ligands.” Physical Review E, vol. 99, no. 2, 022423, American Physical Society, 2019, doi:10.1103/PhysRevE.99.022423. short: M. Carballo-Pacheco, J. Desponds, T. Gavrilchenko, A. Mayer, R. Prizak, G. Reddy, I. Nemenman, T. Mora, Physical Review E 99 (2019). date_created: 2019-03-10T22:59:20Z date_published: 2019-02-26T00:00:00Z date_updated: 2024-02-28T13:12:06Z day: '26' department: - _id: NiBa - _id: GaTk doi: 10.1103/PhysRevE.99.022423 external_id: isi: - '000459916500007' intvolume: ' 99' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/448118v1.abstract month: '02' oa: 1 oa_version: Preprint publication: Physical Review E publication_status: published publisher: American Physical Society quality_controlled: '1' scopus_import: '1' status: public title: Receptor crosstalk improves concentration sensing of multiple ligands type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 99 year: '2019' ... --- _id: '7606' abstract: - lang: eng text: We derive a tight lower bound on equivocation (conditional entropy), or equivalently a tight upper bound on mutual information between a signal variable and channel outputs. The bound is in terms of the joint distribution of the signals and maximum a posteriori decodes (most probable signals given channel output). As part of our derivation, we describe the key properties of the distribution of signals, channel outputs and decodes, that minimizes equivocation and maximizes mutual information. This work addresses a problem in data analysis, where mutual information between signals and decodes is sometimes used to lower bound the mutual information between signals and channel outputs. Our result provides a corresponding upper bound. article_number: '8989292' article_processing_charge: No author: - first_name: Michal full_name: Hledik, Michal id: 4171253A-F248-11E8-B48F-1D18A9856A87 last_name: Hledik - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: 'Hledik M, Sokolowski TR, Tkačik G. A tight upper bound on mutual information. In: IEEE Information Theory Workshop, ITW 2019. IEEE; 2019. doi:10.1109/ITW44776.2019.8989292' apa: 'Hledik, M., Sokolowski, T. R., & Tkačik, G. (2019). A tight upper bound on mutual information. In IEEE Information Theory Workshop, ITW 2019. Visby, Sweden: IEEE. https://doi.org/10.1109/ITW44776.2019.8989292' chicago: Hledik, Michal, Thomas R Sokolowski, and Gašper Tkačik. “A Tight Upper Bound on Mutual Information.” In IEEE Information Theory Workshop, ITW 2019. IEEE, 2019. https://doi.org/10.1109/ITW44776.2019.8989292. ieee: M. Hledik, T. R. Sokolowski, and G. Tkačik, “A tight upper bound on mutual information,” in IEEE Information Theory Workshop, ITW 2019, Visby, Sweden, 2019. ista: Hledik M, Sokolowski TR, Tkačik G. 2019. A tight upper bound on mutual information. IEEE Information Theory Workshop, ITW 2019. Information Theory Workshop, 8989292. mla: Hledik, Michal, et al. “A Tight Upper Bound on Mutual Information.” IEEE Information Theory Workshop, ITW 2019, 8989292, IEEE, 2019, doi:10.1109/ITW44776.2019.8989292. short: M. Hledik, T.R. Sokolowski, G. Tkačik, in:, IEEE Information Theory Workshop, ITW 2019, IEEE, 2019. conference: end_date: 2019-08-28 location: Visby, Sweden name: Information Theory Workshop start_date: 2019-08-25 date_created: 2020-03-22T23:00:47Z date_published: 2019-08-01T00:00:00Z date_updated: 2024-03-06T14:22:51Z day: '01' department: - _id: GaTk doi: 10.1109/ITW44776.2019.8989292 ec_funded: 1 external_id: arxiv: - '1812.01475' isi: - '000540384500015' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1812.01475 month: '08' oa: 1 oa_version: Preprint project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: IEEE Information Theory Workshop, ITW 2019 publication_identifier: isbn: - '9781538669006' publication_status: published publisher: IEEE quality_controlled: '1' related_material: record: - id: '15020' relation: dissertation_contains status: public scopus_import: '1' status: public title: A tight upper bound on mutual information type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ... --- _id: '306' abstract: - lang: eng text: A cornerstone of statistical inference, the maximum entropy framework is being increasingly applied to construct descriptive and predictive models of biological systems, especially complex biological networks, from large experimental data sets. Both its broad applicability and the success it obtained in different contexts hinge upon its conceptual simplicity and mathematical soundness. Here we try to concisely review the basic elements of the maximum entropy principle, starting from the notion of ‘entropy’, and describe its usefulness for the analysis of biological systems. As examples, we focus specifically on the problem of reconstructing gene interaction networks from expression data and on recent work attempting to expand our system-level understanding of bacterial metabolism. Finally, we highlight some extensions and potential limitations of the maximum entropy approach, and point to more recent developments that are likely to play a key role in the upcoming challenges of extracting structures and information from increasingly rich, high-throughput biological data. article_number: e00596 author: - first_name: Andrea full_name: De Martino, Andrea last_name: De Martino - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: De Martino A, De Martino D. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 2018;4(4). doi:10.1016/j.heliyon.2018.e00596 apa: De Martino, A., & De Martino, D. (2018). An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. Elsevier. https://doi.org/10.1016/j.heliyon.2018.e00596 chicago: De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon. Elsevier, 2018. https://doi.org/10.1016/j.heliyon.2018.e00596. ieee: A. De Martino and D. De Martino, “An introduction to the maximum entropy approach and its application to inference problems in biology,” Heliyon, vol. 4, no. 4. Elsevier, 2018. ista: De Martino A, De Martino D. 2018. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 4(4), e00596. mla: De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon, vol. 4, no. 4, e00596, Elsevier, 2018, doi:10.1016/j.heliyon.2018.e00596. short: A. De Martino, D. De Martino, Heliyon 4 (2018). date_created: 2018-12-11T11:45:44Z date_published: 2018-04-01T00:00:00Z date_updated: 2021-01-12T07:40:46Z day: '01' ddc: - '530' department: - _id: GaTk doi: 10.1016/j.heliyon.2018.e00596 ec_funded: 1 file: - access_level: open_access checksum: 67010cf5e3b3e0637c659371714a715a content_type: application/pdf creator: dernst date_created: 2019-02-06T07:36:24Z date_updated: 2020-07-14T12:45:59Z file_id: '5929' file_name: 2018_Heliyon_DeMartino.pdf file_size: 994490 relation: main_file file_date_updated: 2020-07-14T12:45:59Z has_accepted_license: '1' intvolume: ' 4' issue: '4' language: - iso: eng month: '04' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Heliyon publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: 1 status: public title: An introduction to the maximum entropy approach and its application to inference problems in biology tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2018' ... --- _id: '305' abstract: - lang: eng text: The hanging-drop network (HDN) is a technology platform based on a completely open microfluidic network at the bottom of an inverted, surface-patterned substrate. The platform is predominantly used for the formation, culturing, and interaction of self-assembled spherical microtissues (spheroids) under precisely controlled flow conditions. Here, we describe design, fabrication, and operation of microfluidic hanging-drop networks. acknowledgement: This work was financially supported by FP7 of the EU through the project “Body on a chip,” ICT-FET-296257, and the ERC Advanced Grant “NeuroCMOS” (contract 267351), as well as by an individual Ambizione Grant 142440 from the Swiss National Science Foundation for Olivier Frey. The research leading to these results also received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. [291734]. We would like to thank Alexander Stettler, ETH Zurich for his expertise and support in the cleanroom, and we acknowledge the Single Cell Unit of D-BSSE, ETH Zurich for assistance in microscopy issues. M.L. is grateful to the members of the Guet and Tkačik groups, IST Austria, for valuable comments and support. alternative_title: - MIMB author: - first_name: Patrick full_name: Misun, Patrick last_name: Misun - first_name: Axel full_name: Birchler, Axel last_name: Birchler - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Andreas full_name: Hierlemann, Andreas last_name: Hierlemann - first_name: Olivier full_name: Frey, Olivier last_name: Frey citation: ama: Misun P, Birchler A, Lang M, Hierlemann A, Frey O. Fabrication and operation of microfluidic hanging drop networks. Methods in Molecular Biology. 2018;1771:183-202. doi:10.1007/978-1-4939-7792-5_15 apa: Misun, P., Birchler, A., Lang, M., Hierlemann, A., & Frey, O. (2018). Fabrication and operation of microfluidic hanging drop networks. Methods in Molecular Biology. Springer. https://doi.org/10.1007/978-1-4939-7792-5_15 chicago: Misun, Patrick, Axel Birchler, Moritz Lang, Andreas Hierlemann, and Olivier Frey. “Fabrication and Operation of Microfluidic Hanging Drop Networks.” Methods in Molecular Biology. Springer, 2018. https://doi.org/10.1007/978-1-4939-7792-5_15. ieee: P. Misun, A. Birchler, M. Lang, A. Hierlemann, and O. Frey, “Fabrication and operation of microfluidic hanging drop networks,” Methods in Molecular Biology, vol. 1771. Springer, pp. 183–202, 2018. ista: Misun P, Birchler A, Lang M, Hierlemann A, Frey O. 2018. Fabrication and operation of microfluidic hanging drop networks. Methods in Molecular Biology. 1771, 183–202. mla: Misun, Patrick, et al. “Fabrication and Operation of Microfluidic Hanging Drop Networks.” Methods in Molecular Biology, vol. 1771, Springer, 2018, pp. 183–202, doi:10.1007/978-1-4939-7792-5_15. short: P. Misun, A. Birchler, M. Lang, A. Hierlemann, O. Frey, Methods in Molecular Biology 1771 (2018) 183–202. date_created: 2018-12-11T11:45:43Z date_published: 2018-01-01T00:00:00Z date_updated: 2021-01-12T07:40:42Z day: '01' department: - _id: CaGu - _id: GaTk doi: 10.1007/978-1-4939-7792-5_15 ec_funded: 1 intvolume: ' 1771' language: - iso: eng month: '01' oa_version: None page: 183 - 202 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Methods in Molecular Biology publication_status: published publisher: Springer publist_id: '7574' quality_controlled: '1' scopus_import: 1 status: public title: Fabrication and operation of microfluidic hanging drop networks type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 1771 year: '2018' ... --- _id: '281' abstract: - lang: eng text: 'Although cells respond specifically to environments, how environmental identity is encoded intracellularly is not understood. Here, we study this organization of information in budding yeast by estimating the mutual information between environmental transitions and the dynamics of nuclear translocation for 10 transcription factors. Our method of estimation is general, scalable, and based on decoding from single cells. The dynamics of the transcription factors are necessary to encode the highest amounts of extracellular information, and we show that information is transduced through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can encode the nature of multiple stresses, but only if stress is high; specialists (Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly and for a wider range of magnitudes. In particular, Dot6 encodes almost as much information as Msn2, the master regulator of the environmental stress response. Each transcription factor reports differently, and it is only their collective behavior that distinguishes between multiple environmental states. Changes in the dynamics of the localization of transcription factors thus constitute a precise, distributed internal representation of extracellular change. We predict that such multidimensional representations are common in cellular decision-making.' acknowledgement: This work was supported by the Biotechnology and Biological Sciences Research Council (J.M.J.P., I.F., and P.S.S.), the Engineering and Physical Sciences Research Council (EPSRC) (A.A.G.), and Austrian Science Fund Grant FWF P28844 (to G.T.). article_processing_charge: No article_type: original author: - first_name: Alejandro full_name: Granados, Alejandro last_name: Granados - first_name: Julian full_name: Pietsch, Julian last_name: Pietsch - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Isebail full_name: Farquhar, Isebail last_name: Farquhar - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Peter full_name: Swain, Peter last_name: Swain citation: ama: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. Distributed and dynamic intracellular organization of extracellular information. PNAS. 2018;115(23):6088-6093. doi:10.1073/pnas.1716659115 apa: Granados, A., Pietsch, J., Cepeda Humerez, S. A., Farquhar, I., Tkačik, G., & Swain, P. (2018). Distributed and dynamic intracellular organization of extracellular information. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1716659115 chicago: Granados, Alejandro, Julian Pietsch, Sarah A Cepeda Humerez, Isebail Farquhar, Gašper Tkačik, and Peter Swain. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” PNAS. National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1716659115. ieee: A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkačik, and P. Swain, “Distributed and dynamic intracellular organization of extracellular information,” PNAS, vol. 115, no. 23. National Academy of Sciences, pp. 6088–6093, 2018. ista: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. 2018. Distributed and dynamic intracellular organization of extracellular information. PNAS. 115(23), 6088–6093. mla: Granados, Alejandro, et al. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” PNAS, vol. 115, no. 23, National Academy of Sciences, 2018, pp. 6088–93, doi:10.1073/pnas.1716659115. short: A. Granados, J. Pietsch, S.A. Cepeda Humerez, I. Farquhar, G. Tkačik, P. Swain, PNAS 115 (2018) 6088–6093. date_created: 2018-12-11T11:45:35Z date_published: 2018-06-05T00:00:00Z date_updated: 2023-09-11T12:58:24Z day: '05' department: - _id: GaTk doi: 10.1073/pnas.1716659115 external_id: isi: - '000434114900071' pmid: - '29784812' intvolume: ' 115' isi: 1 issue: '23' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/early/2017/09/21/192039 month: '06' oa: 1 oa_version: Preprint page: 6088 - 6093 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '7618' quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: '1' status: public title: Distributed and dynamic intracellular organization of extracellular information type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 115 year: '2018' ... --- _id: '316' abstract: - lang: eng text: 'Self-incompatibility (SI) is a genetically based recognition system that functions to prevent self-fertilization and mating among related plants. An enduring puzzle in SI is how the high diversity observed in nature arises and is maintained. Based on the underlying recognition mechanism, SI can be classified into two main groups: self- and non-self recognition. Most work has focused on diversification within self-recognition systems despite expected differences between the two groups in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic population genetic model and stochastic simulations to investigate how novel S-haplotypes evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI system. For this model the pathways for diversification involve either the maintenance or breakdown of SI and can vary in the order of mutations of the female (SRNase) and male (SLF) components. We show analytically that diversification can occur with high inbreeding depression and self-pollination, but this varies with evolutionary pathway and level of completeness (which determines the number of potential mating partners in the population), and in general is more likely for lower haplotype number. The conditions for diversification are broader in stochastic simulations of finite population size. However, the number of haplotypes observed under high inbreeding and moderate to high self-pollination is less than that commonly observed in nature. Diversification was observed through pathways that maintain SI as well as through self-compatible intermediates. Yet the lifespan of diversified haplotypes was sensitive to their level of completeness. By examining diversification in a non-self recognition SI system, this model extends our understanding of the evolution and maintenance of haplotype diversity observed in a self recognition system common in flowering plants.' article_processing_charge: No article_type: original author: - first_name: Katarina full_name: Bodova, Katarina id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bodova orcid: 0000-0002-7214-0171 - first_name: Tadeas full_name: Priklopil, Tadeas id: 3C869AA0-F248-11E8-B48F-1D18A9856A87 last_name: Priklopil - first_name: David full_name: Field, David id: 419049E2-F248-11E8-B48F-1D18A9856A87 last_name: Field orcid: 0000-0002-4014-8478 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Melinda full_name: Pickup, Melinda id: 2C78037E-F248-11E8-B48F-1D18A9856A87 last_name: Pickup orcid: 0000-0001-6118-0541 citation: ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 2018;209(3):861-883. doi:10.1534/genetics.118.300748 apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018). Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.118.300748 chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” Genetics. Genetics Society of America, 2018. https://doi.org/10.1534/genetics.118.300748. ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system,” Genetics, vol. 209, no. 3. Genetics Society of America, pp. 861–883, 2018. ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 209(3), 861–883. mla: Bodova, Katarina, et al. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” Genetics, vol. 209, no. 3, Genetics Society of America, 2018, pp. 861–83, doi:10.1534/genetics.118.300748. short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, Genetics 209 (2018) 861–883. date_created: 2018-12-11T11:45:47Z date_published: 2018-07-01T00:00:00Z date_updated: 2023-09-11T13:57:43Z day: '01' department: - _id: NiBa - _id: GaTk doi: 10.1534/genetics.118.300748 ec_funded: 1 external_id: isi: - '000437171700017' intvolume: ' 209' isi: 1 issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/node/80098.abstract month: '07' oa: 1 oa_version: Preprint page: 861-883 project: - _id: 25B36484-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '329960' name: Mating system and the evolutionary dynamics of hybrid zones - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Genetics publication_status: published publisher: Genetics Society of America quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/recognizing-others-but-not-yourself-new-insights-into-the-evolution-of-plant-mating/ record: - id: '9813' relation: research_data status: public scopus_import: '1' status: public title: Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 209 year: '2018' ... --- _id: '9813' abstract: - lang: eng text: 'File S1 contains figures that clarify the following features: (i) effect of population size on the average number/frequency of SI classes, (ii) changes in the minimal completeness deficit in time for a single class, and (iii) diversification diagrams for all studied pathways, including the summary figure for k = 8. File S2 contains the code required for a stochastic simulation of the SLF system with an example. This file also includes the output in the form of figures and tables.' article_processing_charge: No author: - first_name: Katarína full_name: Bod'ová, Katarína id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bod'ová orcid: 0000-0002-7214-0171 - first_name: Tadeas full_name: Priklopil, Tadeas id: 3C869AA0-F248-11E8-B48F-1D18A9856A87 last_name: Priklopil - first_name: David full_name: Field, David id: 419049E2-F248-11E8-B48F-1D18A9856A87 last_name: Field orcid: 0000-0002-4014-8478 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Melinda full_name: Pickup, Melinda id: 2C78037E-F248-11E8-B48F-1D18A9856A87 last_name: Pickup orcid: 0000-0001-6118-0541 citation: ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material for Bodova et al., 2018. 2018. doi:10.25386/genetics.6148304.v1 apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018). Supplemental material for Bodova et al., 2018. Genetics Society of America. https://doi.org/10.25386/genetics.6148304.v1 chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society of America, 2018. https://doi.org/10.25386/genetics.6148304.v1. ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental material for Bodova et al., 2018.” Genetics Society of America, 2018. ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material for Bodova et al., 2018, Genetics Society of America, 10.25386/genetics.6148304.v1. mla: Bodova, Katarina, et al. Supplemental Material for Bodova et Al., 2018. Genetics Society of America, 2018, doi:10.25386/genetics.6148304.v1. short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018). date_created: 2021-08-06T13:04:32Z date_published: 2018-04-30T00:00:00Z date_updated: 2023-09-11T13:57:42Z day: '30' department: - _id: NiBa - _id: GaTk doi: 10.25386/genetics.6148304.v1 main_file_link: - open_access: '1' url: https://doi.org/10.25386/genetics.6148304.v1 month: '04' oa: 1 oa_version: Published Version publisher: Genetics Society of America related_material: record: - id: '316' relation: used_in_publication status: public status: public title: Supplemental material for Bodova et al., 2018 type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2018' ... --- _id: '406' abstract: - lang: eng text: 'Recent developments in automated tracking allow uninterrupted, high-resolution recording of animal trajectories, sometimes coupled with the identification of stereotyped changes of body pose or other behaviors of interest. Analysis and interpretation of such data represents a challenge: the timing of animal behaviors may be stochastic and modulated by kinematic variables, by the interaction with the environment or with the conspecifics within the animal group, and dependent on internal cognitive or behavioral state of the individual. Existing models for collective motion typically fail to incorporate the discrete, stochastic, and internal-state-dependent aspects of behavior, while models focusing on individual animal behavior typically ignore the spatial aspects of the problem. Here we propose a probabilistic modeling framework to address this gap. Each animal can switch stochastically between different behavioral states, with each state resulting in a possibly different law of motion through space. Switching rates for behavioral transitions can depend in a very general way, which we seek to identify from data, on the effects of the environment as well as the interaction between the animals. We represent the switching dynamics as a Generalized Linear Model and show that: (i) forward simulation of multiple interacting animals is possible using a variant of the Gillespie’s Stochastic Simulation Algorithm; (ii) formulated properly, the maximum likelihood inference of switching rate functions is tractably solvable by gradient descent; (iii) model selection can be used to identify factors that modulate behavioral state switching and to appropriately adjust model complexity to data. To illustrate our framework, we apply it to two synthetic models of animal motion and to real zebrafish tracking data. ' acknowledgement: This work was supported by the Human Frontier Science Program RGP0065/2012 (GT, ES). article_processing_charge: Yes author: - first_name: Katarína full_name: Bod’Ová, Katarína last_name: Bod’Ová - first_name: Gabriel full_name: Mitchell, Gabriel id: 315BCD80-F248-11E8-B48F-1D18A9856A87 last_name: Mitchell - first_name: Roy full_name: Harpaz, Roy last_name: Harpaz - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Probabilistic models of individual and collective animal behavior. PLoS One. 2018;13(3). doi:10.1371/journal.pone.0193049 apa: Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., & Tkačik, G. (2018). Probabilistic models of individual and collective animal behavior. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0193049 chicago: Bod’Ová, Katarína, Gabriel Mitchell, Roy Harpaz, Elad Schneidman, and Gašper Tkačik. “Probabilistic Models of Individual and Collective Animal Behavior.” PLoS One. Public Library of Science, 2018. https://doi.org/10.1371/journal.pone.0193049. ieee: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkačik, “Probabilistic models of individual and collective animal behavior,” PLoS One, vol. 13, no. 3. Public Library of Science, 2018. ista: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. 2018. Probabilistic models of individual and collective animal behavior. PLoS One. 13(3). mla: Bod’Ová, Katarína, et al. “Probabilistic Models of Individual and Collective Animal Behavior.” PLoS One, vol. 13, no. 3, Public Library of Science, 2018, doi:10.1371/journal.pone.0193049. short: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, PLoS One 13 (2018). date_created: 2018-12-11T11:46:18Z date_published: 2018-03-07T00:00:00Z date_updated: 2023-09-15T12:06:19Z day: '07' ddc: - '530' - '571' department: - _id: GaTk doi: 10.1371/journal.pone.0193049 external_id: isi: - '000426896800032' file: - access_level: open_access checksum: 684229493db75b43e98a46cd922da497 content_type: application/pdf creator: system date_created: 2018-12-12T10:15:43Z date_updated: 2020-07-14T12:46:22Z file_id: '5165' file_name: IST-2018-995-v1+1_2018_Bodova_Probabilistic.pdf file_size: 6887358 relation: main_file file_date_updated: 2020-07-14T12:46:22Z has_accepted_license: '1' intvolume: ' 13' isi: 1 issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Submitted Version project: - _id: 255008E4-B435-11E9-9278-68D0E5697425 grant_number: RGP0065/2012 name: Information processing and computation in fish groups publication: PLoS One publication_status: published publisher: Public Library of Science publist_id: '7423' pubrep_id: '995' quality_controlled: '1' related_material: record: - id: '9831' relation: research_data status: public scopus_import: '1' status: public title: Probabilistic models of individual and collective animal behavior tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 13 year: '2018' ... --- _id: '457' abstract: - lang: eng text: Temperate bacteriophages integrate in bacterial genomes as prophages and represent an important source of genetic variation for bacterial evolution, frequently transmitting fitness-augmenting genes such as toxins responsible for virulence of major pathogens. However, only a fraction of bacteriophage infections are lysogenic and lead to prophage acquisition, whereas the majority are lytic and kill the infected bacteria. Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity to bacteriophages are expected to act as a double-edged sword and increase the odds of survival at the cost of depriving bacteria of potentially beneficial prophages. We show that although restriction-modification systems as mechanisms of innate immunity prevent both lytic and lysogenic infections indiscriminately in individual bacteria, they increase the number of prophage-acquiring individuals at the population level. We find that this counterintuitive result is a consequence of phage-host population dynamics, in which restriction-modification systems delay infection onset until bacteria reach densities at which the probability of lysogeny increases. These results underscore the importance of population-level dynamics as a key factor modulating costs and benefits of immunity to temperate bacteriophages article_processing_charge: No author: - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Dominik full_name: Refardt, Dominik last_name: Refardt - first_name: Bruce full_name: Levin, Bruce last_name: Levin - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Pleska M, Lang M, Refardt D, Levin B, Guet CC. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. 2018;2(2):359-366. doi:10.1038/s41559-017-0424-z apa: Pleska, M., Lang, M., Refardt, D., Levin, B., & Guet, C. C. (2018). Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. Springer Nature. https://doi.org/10.1038/s41559-017-0424-z chicago: Pleska, Maros, Moritz Lang, Dominik Refardt, Bruce Levin, and Calin C Guet. “Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with Innate Immunity.” Nature Ecology and Evolution. Springer Nature, 2018. https://doi.org/10.1038/s41559-017-0424-z. ieee: M. Pleska, M. Lang, D. Refardt, B. Levin, and C. C. Guet, “Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity,” Nature Ecology and Evolution, vol. 2, no. 2. Springer Nature, pp. 359–366, 2018. ista: Pleska M, Lang M, Refardt D, Levin B, Guet CC. 2018. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. 2(2), 359–366. mla: Pleska, Maros, et al. “Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with Innate Immunity.” Nature Ecology and Evolution, vol. 2, no. 2, Springer Nature, 2018, pp. 359–66, doi:10.1038/s41559-017-0424-z. short: M. Pleska, M. Lang, D. Refardt, B. Levin, C.C. Guet, Nature Ecology and Evolution 2 (2018) 359–366. date_created: 2018-12-11T11:46:35Z date_published: 2018-02-01T00:00:00Z date_updated: 2023-09-15T12:04:57Z day: '01' department: - _id: CaGu - _id: GaTk doi: 10.1038/s41559-017-0424-z ec_funded: 1 external_id: isi: - '000426516400027' intvolume: ' 2' isi: 1 issue: '2' language: - iso: eng month: '02' oa_version: None page: 359 - 366 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 251BCBEC-B435-11E9-9278-68D0E5697425 grant_number: RGY0079/2011 name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems (HFSP Young investigators' grant) - _id: 251D65D8-B435-11E9-9278-68D0E5697425 grant_number: '24210' name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level (DOC Fellowship) publication: Nature Ecology and Evolution publication_status: published publisher: Springer Nature publist_id: '7364' quality_controlled: '1' related_material: record: - id: '202' relation: dissertation_contains status: public scopus_import: '1' status: public title: Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2 year: '2018' ... --- _id: '9831' abstract: - lang: eng text: 'Implementation of the inference method in Matlab, including three applications of the method: The first one for the model of ant motion, the second one for bacterial chemotaxis, and the third one for the motion of fish.' article_processing_charge: No author: - first_name: Katarína full_name: Bod’Ová, Katarína last_name: Bod’Ová - first_name: Gabriel full_name: Mitchell, Gabriel id: 315BCD80-F248-11E8-B48F-1D18A9856A87 last_name: Mitchell - first_name: Roy full_name: Harpaz, Roy last_name: Harpaz - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Implementation of the inference method in Matlab. 2018. doi:10.1371/journal.pone.0193049.s001 apa: Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., & Tkačik, G. (2018). Implementation of the inference method in Matlab. Public Library of Science. https://doi.org/10.1371/journal.pone.0193049.s001 chicago: Bod’Ová, Katarína, Gabriel Mitchell, Roy Harpaz, Elad Schneidman, and Gašper Tkačik. “Implementation of the Inference Method in Matlab.” Public Library of Science, 2018. https://doi.org/10.1371/journal.pone.0193049.s001. ieee: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkačik, “Implementation of the inference method in Matlab.” Public Library of Science, 2018. ista: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. 2018. Implementation of the inference method in Matlab, Public Library of Science, 10.1371/journal.pone.0193049.s001. mla: Bod’Ová, Katarína, et al. Implementation of the Inference Method in Matlab. Public Library of Science, 2018, doi:10.1371/journal.pone.0193049.s001. short: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, (2018). date_created: 2021-08-09T07:01:24Z date_published: 2018-03-07T00:00:00Z date_updated: 2023-09-15T12:06:18Z day: '07' department: - _id: GaTk doi: 10.1371/journal.pone.0193049.s001 month: '03' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '406' relation: used_in_publication status: public status: public title: Implementation of the inference method in Matlab type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2018' ... --- _id: '31' abstract: - lang: eng text: Correlations in sensory neural networks have both extrinsic and intrinsic origins. Extrinsic or stimulus correlations arise from shared inputs to the network and, thus, depend strongly on the stimulus ensemble. Intrinsic or noise correlations reflect biophysical mechanisms of interactions between neurons, which are expected to be robust to changes in the stimulus ensemble. Despite the importance of this distinction for understanding how sensory networks encode information collectively, no method exists to reliably separate intrinsic interactions from extrinsic correlations in neural activity data, limiting our ability to build predictive models of the network response. In this paper we introduce a general strategy to infer population models of interacting neurons that collectively encode stimulus information. The key to disentangling intrinsic from extrinsic correlations is to infer the couplings between neurons separately from the encoding model and to combine the two using corrections calculated in a mean-field approximation. We demonstrate the effectiveness of this approach in retinal recordings. The same coupling network is inferred from responses to radically different stimulus ensembles, showing that these couplings indeed reflect stimulus-independent interactions between neurons. The inferred model predicts accurately the collective response of retinal ganglion cell populations as a function of the stimulus. acknowledgement: This work was supported by ANR Trajectory, the French State program Investissements d’Avenir managed by the Agence Nationale de la Recherche (LIFESENSES; ANR-10-LABX-65), EC Grant No. H2020-785907 from the Human Brain Project, NIH Grant No. U01NS090501, and an AVIESAN-UNADEV grant to O.M. M.C. was supported by the Agence Nationale de la Recherche Jeune Chercheur/Jeune Chercheuse grant (ANR-17-CE37-0013). article_number: '042410' article_processing_charge: No article_type: original author: - first_name: Ulisse full_name: Ferrari, Ulisse last_name: Ferrari - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Matthew J full_name: Chalk, Matthew J last_name: Chalk - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Thierry full_name: Mora, Thierry last_name: Mora citation: ama: Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. 2018;98(4). doi:10.1103/PhysRevE.98.042410 apa: Ferrari, U., Deny, S., Chalk, M. J., Tkačik, G., Marre, O., & Mora, T. (2018). Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.98.042410 chicago: Ferrari, Ulisse, Stephane Deny, Matthew J Chalk, Gašper Tkačik, Olivier Marre, and Thierry Mora. “Separating Intrinsic Interactions from Extrinsic Correlations in a Network of Sensory Neurons.” Physical Review E. American Physical Society, 2018. https://doi.org/10.1103/PhysRevE.98.042410. ieee: U. Ferrari, S. Deny, M. J. Chalk, G. Tkačik, O. Marre, and T. Mora, “Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons,” Physical Review E, vol. 98, no. 4. American Physical Society, 2018. ista: Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. 2018. Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. 98(4), 042410. mla: Ferrari, Ulisse, et al. “Separating Intrinsic Interactions from Extrinsic Correlations in a Network of Sensory Neurons.” Physical Review E, vol. 98, no. 4, 042410, American Physical Society, 2018, doi:10.1103/PhysRevE.98.042410. short: U. Ferrari, S. Deny, M.J. Chalk, G. Tkačik, O. Marre, T. Mora, Physical Review E 98 (2018). date_created: 2018-12-11T11:44:15Z date_published: 2018-10-17T00:00:00Z date_updated: 2023-09-18T09:18:44Z day: '17' department: - _id: GaTk doi: 10.1103/PhysRevE.98.042410 ec_funded: 1 external_id: isi: - '000447486100004' intvolume: ' 98' isi: 1 issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/243816v2.full month: '10' oa: 1 oa_version: Preprint project: - _id: 26436750-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '785907' name: Human Brain Project Specific Grant Agreement 2 (HBP SGA 2) publication: Physical Review E publication_identifier: issn: - '24700045' publication_status: published publisher: American Physical Society publist_id: '8024' quality_controlled: '1' scopus_import: '1' status: public title: Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 98 year: '2018' ... --- _id: '543' abstract: - lang: eng text: A central goal in theoretical neuroscience is to predict the response properties of sensory neurons from first principles. To this end, “efficient coding” posits that sensory neurons encode maximal information about their inputs given internal constraints. There exist, however, many variants of efficient coding (e.g., redundancy reduction, different formulations of predictive coding, robust coding, sparse coding, etc.), differing in their regimes of applicability, in the relevance of signals to be encoded, and in the choice of constraints. It is unclear how these types of efficient coding relate or what is expected when different coding objectives are combined. Here we present a unified framework that encompasses previously proposed efficient coding models and extends to unique regimes. We show that optimizing neural responses to encode predictive information can lead them to either correlate or decorrelate their inputs, depending on the stimulus statistics; in contrast, at low noise, efficiently encoding the past always predicts decorrelation. Later, we investigate coding of naturalistic movies and show that qualitatively different types of visual motion tuning and levels of response sparsity are predicted, depending on whether the objective is to recover the past or predict the future. Our approach promises a way to explain the observed diversity of sensory neural responses, as due to multiple functional goals and constraints fulfilled by different cell types and/or circuits. article_processing_charge: No author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Chalk MJ, Marre O, Tkačik G. Toward a unified theory of efficient, predictive, and sparse coding. PNAS. 2018;115(1):186-191. doi:10.1073/pnas.1711114115 apa: Chalk, M. J., Marre, O., & Tkačik, G. (2018). Toward a unified theory of efficient, predictive, and sparse coding. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1711114115 chicago: Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Toward a Unified Theory of Efficient, Predictive, and Sparse Coding.” PNAS. National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1711114115. ieee: M. J. Chalk, O. Marre, and G. Tkačik, “Toward a unified theory of efficient, predictive, and sparse coding,” PNAS, vol. 115, no. 1. National Academy of Sciences, pp. 186–191, 2018. ista: Chalk MJ, Marre O, Tkačik G. 2018. Toward a unified theory of efficient, predictive, and sparse coding. PNAS. 115(1), 186–191. mla: Chalk, Matthew J., et al. “Toward a Unified Theory of Efficient, Predictive, and Sparse Coding.” PNAS, vol. 115, no. 1, National Academy of Sciences, 2018, pp. 186–91, doi:10.1073/pnas.1711114115. short: M.J. Chalk, O. Marre, G. Tkačik, PNAS 115 (2018) 186–191. date_created: 2018-12-11T11:47:04Z date_published: 2018-01-02T00:00:00Z date_updated: 2023-09-19T10:16:35Z day: '02' department: - _id: GaTk doi: 10.1073/pnas.1711114115 external_id: isi: - '000419128700049' intvolume: ' 115' isi: 1 issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: 'https://doi.org/10.1101/152660 ' month: '01' oa: 1 oa_version: Submitted Version page: 186 - 191 project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '7273' quality_controlled: '1' scopus_import: '1' status: public title: Toward a unified theory of efficient, predictive, and sparse coding type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 115 year: '2018' ... --- _id: '607' abstract: - lang: eng text: We study the Fokker-Planck equation derived in the large system limit of the Markovian process describing the dynamics of quantitative traits. The Fokker-Planck equation is posed on a bounded domain and its transport and diffusion coefficients vanish on the domain's boundary. We first argue that, despite this degeneracy, the standard no-flux boundary condition is valid. We derive the weak formulation of the problem and prove the existence and uniqueness of its solutions by constructing the corresponding contraction semigroup on a suitable function space. Then, we prove that for the parameter regime with high enough mutation rate the problem exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next, we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt) method for approximation of observables (moments) of the Fokker-Planck solution, which can be interpreted as a nonlinear Galerkin approximation. The limited applicability of the DynMaxEnt method inspires us to introduce its modified version that is valid for the whole range of admissible parameters. Finally, we present several numerical experiments to demonstrate the performance of both the original and modified DynMaxEnt methods. We observe that in the parameter regimes where both methods are valid, the modified one exhibits slightly better approximation properties compared to the original one. acknowledgement: "JH and PM are funded by KAUST baseline funds and grant no. 1000000193 .\r\nWe thank Nicholas Barton (IST Austria) for his useful comments and suggestions. \r\n\r\n" article_processing_charge: No author: - first_name: Katarina full_name: Bodova, Katarina id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bodova orcid: 0000-0002-7214-0171 - first_name: Jan full_name: Haskovec, Jan last_name: Haskovec - first_name: Peter full_name: Markowich, Peter last_name: Markowich citation: ama: 'Bodova K, Haskovec J, Markowich P. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. 2018;376-377:108-120. doi:10.1016/j.physd.2017.10.015' apa: 'Bodova, K., Haskovec, J., & Markowich, P. (2018). Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. Elsevier. https://doi.org/10.1016/j.physd.2017.10.015' chicago: 'Bodova, Katarina, Jan Haskovec, and Peter Markowich. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” Physica D: Nonlinear Phenomena. Elsevier, 2018. https://doi.org/10.1016/j.physd.2017.10.015.' ieee: 'K. Bodova, J. Haskovec, and P. Markowich, “Well posedness and maximum entropy approximation for the dynamics of quantitative traits,” Physica D: Nonlinear Phenomena, vol. 376–377. Elsevier, pp. 108–120, 2018.' ista: 'Bodova K, Haskovec J, Markowich P. 2018. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. 376–377, 108–120.' mla: 'Bodova, Katarina, et al. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” Physica D: Nonlinear Phenomena, vol. 376–377, Elsevier, 2018, pp. 108–20, doi:10.1016/j.physd.2017.10.015.' short: 'K. Bodova, J. Haskovec, P. Markowich, Physica D: Nonlinear Phenomena 376–377 (2018) 108–120.' date_created: 2018-12-11T11:47:28Z date_published: 2018-08-01T00:00:00Z date_updated: 2023-09-19T10:38:34Z day: '01' department: - _id: NiBa - _id: GaTk doi: 10.1016/j.physd.2017.10.015 external_id: arxiv: - '1704.08757' isi: - '000437962900012' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1704.08757 month: '08' oa: 1 oa_version: Submitted Version page: 108-120 publication: 'Physica D: Nonlinear Phenomena' publication_status: published publisher: Elsevier publist_id: '7198' quality_controlled: '1' scopus_import: '1' status: public title: Well posedness and maximum entropy approximation for the dynamics of quantitative traits type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 376-377 year: '2018' ... --- _id: '19' abstract: - lang: eng text: Bacteria regulate genes to survive antibiotic stress, but regulation can be far from perfect. When regulation is not optimal, mutations that change gene expression can contribute to antibiotic resistance. It is not systematically understood to what extent natural gene regulation is or is not optimal for distinct antibiotics, and how changes in expression of specific genes quantitatively affect antibiotic resistance. Here we discover a simple quantitative relation between fitness, gene expression, and antibiotic potency, which rationalizes our observation that a multitude of genes and even innate antibiotic defense mechanisms have expression that is critically nonoptimal under antibiotic treatment. First, we developed a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression and knockout libraries, finding that resistance to a range of 31 antibiotics could result from changing expression of a large and functionally diverse set of genes, in a primarily but not exclusively drug-specific manner. Second, by synthetically controlling the expression of single-drug and multidrug resistance genes, we observed that their fitness-expression functions changed dramatically under antibiotic treatment in accordance with a log-sensitivity relation. Thus, because many genes are nonoptimally expressed under antibiotic treatment, many regulatory mutations can contribute to resistance by altering expression and by activating latent defenses. article_processing_charge: No article_type: original author: - first_name: Adam full_name: Palmer, Adam last_name: Palmer - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Roy full_name: Kishony, Roy last_name: Kishony citation: ama: Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. 2018;35(11):2669-2684. doi:10.1093/molbev/msy163 apa: Palmer, A., Chait, R. P., & Kishony, R. (2018). Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. Oxford University Press. https://doi.org/10.1093/molbev/msy163 chicago: Palmer, Adam, Remy P Chait, and Roy Kishony. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and Evolution. Oxford University Press, 2018. https://doi.org/10.1093/molbev/msy163. ieee: A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates latent potential for antibiotic resistance,” Molecular Biology and Evolution, vol. 35, no. 11. Oxford University Press, pp. 2669–2684, 2018. ista: Palmer A, Chait RP, Kishony R. 2018. Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. 35(11), 2669–2684. mla: Palmer, Adam, et al. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and Evolution, vol. 35, no. 11, Oxford University Press, 2018, pp. 2669–84, doi:10.1093/molbev/msy163. short: A. Palmer, R.P. Chait, R. Kishony, Molecular Biology and Evolution 35 (2018) 2669–2684. date_created: 2018-12-11T11:44:11Z date_published: 2018-08-28T00:00:00Z date_updated: 2023-10-17T11:51:06Z day: '28' department: - _id: CaGu - _id: GaTk doi: 10.1093/molbev/msy163 external_id: isi: - '000452567200006' pmid: - '30169679' intvolume: ' 35' isi: 1 issue: '11' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pubmed/30169679 month: '08' oa: 1 oa_version: Submitted Version page: 2669 - 2684 pmid: 1 publication: Molecular Biology and Evolution publication_identifier: issn: - 0737-4038 publication_status: published publisher: Oxford University Press publist_id: '8036' quality_controlled: '1' scopus_import: '1' status: public title: Nonoptimal gene expression creates latent potential for antibiotic resistance type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2018' ... --- _id: '292' abstract: - lang: eng text: 'Retina is a paradigmatic system for studying sensory encoding: the transformation of light into spiking activity of ganglion cells. The inverse problem, where stimulus is reconstructed from spikes, has received less attention, especially for complex stimuli that should be reconstructed “pixel-by-pixel”. We recorded around a hundred neurons from a dense patch in a rat retina and decoded movies of multiple small randomly-moving discs. We constructed nonlinear (kernelized and neural network) decoders that improved significantly over linear results. An important contribution to this was the ability of nonlinear decoders to reliably separate between neural responses driven by locally fluctuating light signals, and responses at locally constant light driven by spontaneous-like activity. This improvement crucially depended on the precise, non-Poisson temporal structure of individual spike trains, which originated in the spike-history dependence of neural responses. We propose a general principle by which downstream circuitry could discriminate between spontaneous and stimulus-driven activity based solely on higher-order statistical structure in the incoming spike trains.' article_number: e1006057 article_processing_charge: Yes article_type: original author: - first_name: Vicent full_name: Botella Soler, Vicent id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Georg S full_name: Martius, Georg S last_name: Martius - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational Biology. 2018;14(5). doi:10.1371/journal.pcbi.1006057 apa: Botella Soler, V., Deny, S., Martius, G. S., Marre, O., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1006057 chicago: Botella Soler, Vicente, Stephane Deny, Georg S Martius, Olivier Marre, and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” PLoS Computational Biology. Public Library of Science, 2018. https://doi.org/10.1371/journal.pcbi.1006057. ieee: V. Botella Soler, S. Deny, G. S. Martius, O. Marre, and G. Tkačik, “Nonlinear decoding of a complex movie from the mammalian retina,” PLoS Computational Biology, vol. 14, no. 5. Public Library of Science, 2018. ista: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. 2018. Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational Biology. 14(5), e1006057. mla: Botella Soler, Vicente, et al. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” PLoS Computational Biology, vol. 14, no. 5, e1006057, Public Library of Science, 2018, doi:10.1371/journal.pcbi.1006057. short: V. Botella Soler, S. Deny, G.S. Martius, O. Marre, G. Tkačik, PLoS Computational Biology 14 (2018). date_created: 2018-12-11T11:45:39Z date_published: 2018-05-10T00:00:00Z date_updated: 2024-02-21T13:45:25Z day: '10' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1006057 ec_funded: 1 external_id: isi: - '000434012100002' file: - access_level: open_access checksum: 3026f94d235219e15514505fdbadf34e content_type: application/pdf creator: dernst date_created: 2019-02-13T11:07:15Z date_updated: 2020-07-14T12:45:53Z file_id: '5974' file_name: 2018_Plos_Botella_Soler.pdf file_size: 3460786 relation: main_file file_date_updated: 2020-07-14T12:45:53Z has_accepted_license: '1' intvolume: ' 14' isi: 1 issue: '5' language: - iso: eng month: '05' oa: 1 oa_version: Published Version project: - _id: 25CBA828-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '720270' name: Human Brain Project Specific Grant Agreement 1 (HBP SGA 1) - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/video-of-moving-discs-reconstructed-from-rat-retinal-neuron-signals/ record: - id: '5584' relation: research_data status: public scopus_import: '1' status: public title: Nonlinear decoding of a complex movie from the mammalian retina tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 14 year: '2018' ... --- _id: '5584' abstract: - lang: eng text: "This package contains data for the publication \"Nonlinear decoding of a complex movie from the mammalian retina\" by Deny S. et al, PLOS Comput Biol (2018). \r\n\r\nThe data consists of\r\n(i) 91 spike sorted, isolated rat retinal ganglion cells that pass stability and quality criteria, recorded on the multi-electrode array, in response to the presentation of the complex movie with many randomly moving dark discs. The responses are represented as 648000 x 91 binary matrix, where the first index indicates the timebin of duration 12.5 ms, and the second index the neural identity. The matrix entry is 0/1 if the neuron didn't/did spike in the particular time bin.\r\n(ii) README file and a graphical illustration of the structure of the experiment, specifying how the 648000 timebins are split into epochs where 1, 2, 4, or 10 discs were displayed, and which stimulus segments are exact repeats or unique ball trajectories.\r\n(iii) a 648000 x 400 matrix of luminance traces for each of the 20 x 20 positions (\"sites\") in the movie frame, with time that is locked to the recorded raster. The luminance traces are produced as described in the manuscript by filtering the raw disc movie with a small gaussian spatial kernel. " article_processing_charge: No author: - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Vicente full_name: Botella-Soler, Vicente last_name: Botella-Soler - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. Nonlinear decoding of a complex movie from the mammalian retina. 2018. doi:10.15479/AT:ISTA:98 apa: Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98 chicago: Deny, Stephane, Olivier Marre, Vicente Botella-Soler, Georg S Martius, and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:98. ieee: S. Deny, O. Marre, V. Botella-Soler, G. S. Martius, and G. Tkačik, “Nonlinear decoding of a complex movie from the mammalian retina.” Institute of Science and Technology Austria, 2018. ista: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. 2018. Nonlinear decoding of a complex movie from the mammalian retina, Institute of Science and Technology Austria, 10.15479/AT:ISTA:98. mla: Deny, Stephane, et al. Nonlinear Decoding of a Complex Movie from the Mammalian Retina. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:98. short: S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkačik, (2018). datarep_id: '98' date_created: 2018-12-12T12:31:39Z date_published: 2018-03-29T00:00:00Z date_updated: 2024-02-21T13:45:26Z day: '29' ddc: - '570' department: - _id: ChLa - _id: GaTk doi: 10.15479/AT:ISTA:98 file: - access_level: open_access checksum: 6808748837b9afbbbabc2a356ca2b88a content_type: application/octet-stream creator: system date_created: 2018-12-12T13:02:24Z date_updated: 2020-07-14T12:47:07Z file_id: '5590' file_name: IST-2018-98-v1+1_BBalls_area2_tile2_20x20.mat file_size: 1142543971 relation: main_file - access_level: open_access checksum: d6d6cd07743038fe3a12352983fcf9dd content_type: application/pdf creator: system date_created: 2018-12-12T13:02:25Z date_updated: 2020-07-14T12:47:07Z file_id: '5591' file_name: IST-2018-98-v1+2_ExperimentStructure.pdf file_size: 702336 relation: main_file - access_level: open_access checksum: 0c9cfb4dab35bb3dc25a04395600b1c8 content_type: application/octet-stream creator: system date_created: 2018-12-12T13:02:26Z date_updated: 2020-07-14T12:47:07Z file_id: '5592' file_name: IST-2018-98-v1+3_GoodLocations_area2_20x20.mat file_size: 432 relation: main_file - access_level: open_access checksum: 2a83b011012e21e934b4596285b1a183 content_type: text/plain creator: system date_created: 2018-12-12T13:02:26Z date_updated: 2020-07-14T12:47:07Z file_id: '5593' file_name: IST-2018-98-v1+4_README.txt file_size: 986 relation: main_file file_date_updated: 2020-07-14T12:47:07Z has_accepted_license: '1' keyword: - retina - decoding - regression - neural networks - complex stimulus license: https://creativecommons.org/publicdomain/zero/1.0/ month: '03' oa: 1 oa_version: Published Version project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publisher: Institute of Science and Technology Austria related_material: record: - id: '292' relation: used_in_publication status: public status: public title: Nonlinear decoding of a complex movie from the mammalian retina tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '161' abstract: - lang: eng text: 'Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells.' article_number: '2988' article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Andersson Anna full_name: Mc, Andersson Anna last_name: Mc - first_name: Tobias full_name: Bergmiller, Tobias id: 2C471CFA-F248-11E8-B48F-1D18A9856A87 last_name: Bergmiller orcid: 0000-0001-5396-4346 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-05417-9 apa: De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018). Statistical mechanics for metabolic networks during steady state growth. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9 chicago: De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet, and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9. ieee: D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical mechanics for metabolic networks during steady state growth,” Nature Communications, vol. 9, no. 1. Springer Nature, 2018. ista: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 9(1), 2988. mla: De Martino, Daniele, et al. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications, vol. 9, no. 1, 2988, Springer Nature, 2018, doi:10.1038/s41467-018-05417-9. short: D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications 9 (2018). date_created: 2018-12-11T11:44:57Z date_published: 2018-07-30T00:00:00Z date_updated: 2024-02-21T13:45:39Z day: '30' ddc: - '570' department: - _id: GaTk - _id: CaGu doi: 10.1038/s41467-018-05417-9 ec_funded: 1 external_id: isi: - '000440149300021' file: - access_level: open_access checksum: 3ba7ab27b27723c7dcf633e8fc1f8f18 content_type: application/pdf creator: dernst date_created: 2018-12-17T16:44:28Z date_updated: 2020-07-14T12:45:06Z file_id: '5728' file_name: 2018_NatureComm_DeMartino.pdf file_size: 1043205 relation: main_file file_date_updated: 2020-07-14T12:45:06Z has_accepted_license: '1' intvolume: ' 9' isi: 1 issue: '1' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Nature Communications publication_status: published publisher: Springer Nature publist_id: '7760' quality_controlled: '1' related_material: record: - id: '5587' relation: popular_science status: public scopus_import: '1' status: public title: Statistical mechanics for metabolic networks during steady state growth tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 9 year: '2018' ... --- _id: '5587' abstract: - lang: eng text: "Supporting material to the article \r\nSTATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH\r\n\r\nboundscoli.dat\r\nFlux Bounds of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium. \r\n\r\npolcoli.dat\r\nMatrix enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium, \r\nobtained from the soichiometric matrix by standard linear algebra (reduced row echelon form).\r\n\r\nellis.dat\r\nApproximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\npoint0.dat\r\nCenter of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\nlovasz.cpp \r\nThis c++ code file receives in input the polytope of the feasible steady states of a metabolic network, \r\n(matrix and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding the polytope\r\nwith the Lovasz method \r\nNB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we refer to PLoS ONE 10.4 e0122670 (2015).\r\n\r\nsampleHRnew.cpp \r\nThis c++ code file receives in input the polytope of the feasible steady states of a metabolic network, \r\n(matrix and bounds), the ellipsoid rounding the polytope, a point inside and \r\nit gives in output a max entropy sampling at fixed average growth rate \r\nof the steady states by performing an Hit-and-Run Monte Carlo Markov chain.\r\nNB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we refer to PLoS ONE 10.4 e0122670 (2015)." article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:10.15479/AT:ISTA:62 apa: De Martino, D., & Tkačik, G. (2018). Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:62 chicago: De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:62. ieee: D. De Martino and G. Tkačik, “Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018. ista: De Martino D, Tkačik G. 2018. Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:62. mla: De Martino, Daniele, and Gašper Tkačik. Supporting Materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:62. short: D. De Martino, G. Tkačik, (2018). datarep_id: '111' date_created: 2018-12-12T12:31:41Z date_published: 2018-09-21T00:00:00Z date_updated: 2024-02-21T13:45:39Z day: '21' ddc: - '530' department: - _id: GaTk doi: 10.15479/AT:ISTA:62 ec_funded: 1 file: - access_level: open_access checksum: 97992e3e8cf8544ec985a48971708726 content_type: application/zip creator: system date_created: 2018-12-12T13:05:13Z date_updated: 2020-07-14T12:47:08Z file_id: '5641' file_name: IST-2018-111-v1+1_CODES.zip file_size: 14376 relation: main_file file_date_updated: 2020-07-14T12:47:08Z has_accepted_license: '1' keyword: - metabolic networks - e.coli core - maximum entropy - monte carlo markov chain sampling - ellipsoidal rounding month: '09' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publisher: Institute of Science and Technology Austria related_material: record: - id: '161' relation: research_paper status: public status: public title: Supporting materials "STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH" tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '67' abstract: - lang: eng text: 'Gene regulatory networks evolve through rewiring of individual components—that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor–DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor–DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.' article_processing_charge: No article_type: original author: - first_name: Claudia full_name: Igler, Claudia id: 46613666-F248-11E8-B48F-1D18A9856A87 last_name: Igler - first_name: Mato full_name: Lagator, Mato id: 345D25EC-F248-11E8-B48F-1D18A9856A87 last_name: Lagator - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Jonathan P full_name: Bollback, Jonathan P id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87 last_name: Bollback orcid: 0000-0002-4624-4612 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2018;2(10):1633-1643. doi:10.1038/s41559-018-0651-y apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018). Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. Nature Publishing Group. https://doi.org/10.1038/s41559-018-0651-y chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin C Guet. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Nature Ecology and Evolution. Nature Publishing Group, 2018. https://doi.org/10.1038/s41559-018-0651-y. ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Evolutionary potential of transcription factors for gene regulatory rewiring,” Nature Ecology and Evolution, vol. 2, no. 10. Nature Publishing Group, pp. 1633–1643, 2018. ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2(10), 1633–1643. mla: Igler, Claudia, et al. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Nature Ecology and Evolution, vol. 2, no. 10, Nature Publishing Group, 2018, pp. 1633–43, doi:10.1038/s41559-018-0651-y. short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, Nature Ecology and Evolution 2 (2018) 1633–1643. date_created: 2018-12-11T11:44:27Z date_published: 2018-09-10T00:00:00Z date_updated: 2024-03-27T23:30:48Z day: '10' ddc: - '570' department: - _id: CaGu - _id: GaTk - _id: JoBo doi: 10.1038/s41559-018-0651-y ec_funded: 1 external_id: isi: - '000447947600021' file: - access_level: open_access checksum: 383a2e2c944a856e2e821ec8e7bf71b6 content_type: application/pdf creator: dernst date_created: 2020-05-14T11:28:52Z date_updated: 2020-07-14T12:47:37Z file_id: '7830' file_name: 2018_NatureEcology_Igler.pdf file_size: 1135973 relation: main_file file_date_updated: 2020-07-14T12:47:37Z has_accepted_license: '1' intvolume: ' 2' isi: 1 issue: '10' language: - iso: eng month: '09' oa: 1 oa_version: Submitted Version page: 1633 - 1643 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2578D616-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '648440' name: Selective Barriers to Horizontal Gene Transfer - _id: 251EE76E-B435-11E9-9278-68D0E5697425 grant_number: '24573' name: Design principles underlying genetic switch architecture (DOC Fellowship) publication: Nature Ecology and Evolution publication_status: published publisher: Nature Publishing Group publist_id: '7987' quality_controlled: '1' related_material: record: - id: '5585' relation: popular_science status: public - id: '6371' relation: dissertation_contains status: public scopus_import: '1' status: public title: Evolutionary potential of transcription factors for gene regulatory rewiring type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2 year: '2018' ... --- _id: '5585' abstract: - lang: eng text: Mean repression values and standard error of the mean are given for all operator mutant libraries. article_processing_charge: No author: - first_name: Claudia full_name: Igler, Claudia id: 46613666-F248-11E8-B48F-1D18A9856A87 last_name: Igler - first_name: Mato full_name: Lagator, Mato id: 345D25EC-F248-11E8-B48F-1D18A9856A87 last_name: Lagator - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Jonathan P full_name: Bollback, Jonathan P id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87 last_name: Bollback orcid: 0000-0002-4624-4612 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring. 2018. doi:10.15479/AT:ISTA:108 apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018). Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:108 chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin C Guet. “Data for the Paper Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:108. ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring.” Institute of Science and Technology Austria, 2018. ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring, Institute of Science and Technology Austria, 10.15479/AT:ISTA:108. mla: Igler, Claudia, et al. Data for the Paper Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:108. short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, (2018). datarep_id: '108' date_created: 2018-12-12T12:31:40Z date_published: 2018-07-20T00:00:00Z date_updated: 2024-03-27T23:30:48Z day: '20' ddc: - '576' department: - _id: CaGu - _id: GaTk doi: 10.15479/AT:ISTA:108 ec_funded: 1 file: - access_level: open_access checksum: 1435781526c77413802adee0d4583cce content_type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet creator: system date_created: 2018-12-12T13:02:45Z date_updated: 2020-07-14T12:47:07Z file_id: '5611' file_name: IST-2018-108-v1+1_data_figures.xlsx file_size: 16507 relation: main_file file_date_updated: 2020-07-14T12:47:07Z has_accepted_license: '1' month: '07' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2578D616-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '648440' name: Selective Barriers to Horizontal Gene Transfer - _id: 251EE76E-B435-11E9-9278-68D0E5697425 grant_number: '24573' name: Design principles underlying genetic switch architecture (DOC Fellowship) publisher: Institute of Science and Technology Austria related_material: record: - id: '67' relation: research_paper status: public - id: '6371' relation: research_paper status: public status: public title: Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '613' abstract: - lang: eng text: 'Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.' acknowledgement: We are grateful to M. Lang, H. Janovjak, M. Khammash, A. Milias-Argeitis, M. Rullan, G. Batt, A. Bosma-Moody, Aryan, S. Leibler, and members of the Guet and Tkačik groups for helpful discussion, comments, and suggestions. We thank A. Moglich, T. Mathes, J. Tabor, and S. Schmidl for kind gifts of strains, and R. Hauschild, B. Knep, M. Lang, T. Asenov, E. Papusheva, T. Menner, T. Adletzberger, and J. Merrin for technical assistance. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. (to R.C. and J.R.), Austrian Science Fund grant FWF P28844 (to G.T.), and internal IST Austria Interdisciplinary Project Support. J.R. acknowledges support from the Agence Nationale de la Recherche (ANR) under Grant Nos. ANR-16-CE33-0018 (MEMIP), ANR-16-CE12-0025 (COGEX) and ANR-10-BINF-06-01 (ICEBERG). article_number: '1535' article_processing_charge: Yes (in subscription journal) author: - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Tobias full_name: Bergmiller, Tobias id: 2C471CFA-F248-11E8-B48F-1D18A9856A87 last_name: Bergmiller orcid: 0000-0001-5396-4346 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-01683-1 apa: Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., & Guet, C. C. (2017). Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-01683-1 chicago: Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-01683-1. ieee: R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping bacterial population behavior through computer interfaced control of individual cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017. ista: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 8(1), 1535. mla: Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications, vol. 8, no. 1, 1535, Nature Publishing Group, 2017, doi:10.1038/s41467-017-01683-1. short: R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications 8 (2017). date_created: 2018-12-11T11:47:30Z date_published: 2017-12-01T00:00:00Z date_updated: 2021-01-12T08:06:15Z day: '01' ddc: - '576' - '579' department: - _id: CaGu - _id: GaTk doi: 10.1038/s41467-017-01683-1 ec_funded: 1 file: - access_level: open_access checksum: 44bb5d0229926c23a9955d9fe0f9723f content_type: application/pdf creator: system date_created: 2018-12-12T10:16:05Z date_updated: 2020-07-14T12:47:20Z file_id: '5190' file_name: IST-2017-911-v1+1_s41467-017-01683-1.pdf file_size: 1951699 relation: main_file file_date_updated: 2020-07-14T12:47:20Z has_accepted_license: '1' intvolume: ' 8' issue: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '7191' pubrep_id: '911' quality_controlled: '1' scopus_import: 1 status: public title: Shaping bacterial population behavior through computer interfaced control of individual cells tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2017' ... --- _id: '652' abstract: - lang: eng text: 'We present an approach that enables robots to self-organize their sensorimotor behavior from scratch without providing specific information about neither the robot nor its environment. This is achieved by a simple neural control law that increases the consistency between external sensor dynamics and internal neural dynamics of the utterly simple controller. In this way, the embodiment and the agent-environment coupling are the only source of individual development. We show how an anthropomorphic tendon driven arm-shoulder system develops different behaviors depending on that coupling. For instance: Given a bottle half-filled with water, the arm starts to shake it, driven by the physical response of the water. When attaching a brush, the arm can be manipulated into wiping a table, and when connected to a revolvable wheel it finds out how to rotate it. Thus, the robot may be said to discover the affordances of the world. When allowing two (simulated) humanoid robots to interact physically, they engage into a joint behavior development leading to, for instance, spontaneous cooperation. More social effects are observed if the robots can visually perceive each other. Although, as an observer, it is tempting to attribute an apparent intentionality, there is nothing of the kind put in. As a conclusion, we argue that emergent behavior may be much less rooted in explicit intentions, internal motivations, or specific reward systems than is commonly believed.' article_number: '7846789' author: - first_name: Ralf full_name: Der, Ralf last_name: Der - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius citation: ama: 'Der R, Martius GS. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. In: IEEE; 2017. doi:10.1109/DEVLRN.2016.7846789' apa: 'Der, R., & Martius, G. S. (2017). Dynamical self consistency leads to behavioral development and emergent social interactions in robots. Presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789' chicago: Der, Ralf, and Georg S Martius. “Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots.” IEEE, 2017. https://doi.org/10.1109/DEVLRN.2016.7846789. ieee: 'R. Der and G. S. Martius, “Dynamical self consistency leads to behavioral development and emergent social interactions in robots,” presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France, 2017.' ista: 'Der R, Martius GS. 2017. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , 7846789.' mla: Der, Ralf, and Georg S. Martius. Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots. 7846789, IEEE, 2017, doi:10.1109/DEVLRN.2016.7846789. short: R. Der, G.S. Martius, in:, IEEE, 2017. conference: end_date: 2016-09-22 location: Cergy-Pontoise, France name: 'ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics ' start_date: 2016-09-19 date_created: 2018-12-11T11:47:43Z date_published: 2017-02-07T00:00:00Z date_updated: 2021-01-12T08:07:51Z day: '07' department: - _id: ChLa - _id: GaTk doi: 10.1109/DEVLRN.2016.7846789 language: - iso: eng month: '02' oa_version: None publication_identifier: isbn: - 978-150905069-7 publication_status: published publisher: IEEE publist_id: '7100' quality_controlled: '1' scopus_import: 1 status: public title: Dynamical self consistency leads to behavioral development and emergent social interactions in robots type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 year: '2017' ... --- _id: '658' abstract: - lang: eng text: 'With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object''s identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.' article_number: '00008' article_processing_charge: Yes author: - first_name: Ralf full_name: Der, Ralf last_name: Der - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius citation: ama: Der R, Martius GS. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 2017;11(MAR). doi:10.3389/fnbot.2017.00008 apa: Der, R., & Martius, G. S. (2017). Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research Foundation. https://doi.org/10.3389/fnbot.2017.00008 chicago: Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” Frontiers in Neurorobotics. Frontiers Research Foundation, 2017. https://doi.org/10.3389/fnbot.2017.00008. ieee: R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal robots,” Frontiers in Neurorobotics, vol. 11, no. MAR. Frontiers Research Foundation, 2017. ista: Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 11(MAR), 00008. mla: Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” Frontiers in Neurorobotics, vol. 11, no. MAR, 00008, Frontiers Research Foundation, 2017, doi:10.3389/fnbot.2017.00008. short: R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017). date_created: 2018-12-11T11:47:45Z date_published: 2017-03-16T00:00:00Z date_updated: 2021-01-12T08:08:04Z day: '16' ddc: - '006' department: - _id: ChLa - _id: GaTk doi: 10.3389/fnbot.2017.00008 ec_funded: 1 file: - access_level: open_access checksum: b1bc43f96d1df3313c03032c2a46388d content_type: application/pdf creator: system date_created: 2018-12-12T10:18:49Z date_updated: 2020-07-14T12:47:33Z file_id: '5371' file_name: IST-2017-903-v1+1_fnbot-11-00008.pdf file_size: 8439566 relation: main_file file_date_updated: 2020-07-14T12:47:33Z has_accepted_license: '1' intvolume: ' 11' issue: MAR language: - iso: eng month: '03' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Frontiers in Neurorobotics publication_identifier: issn: - '16625218' publication_status: published publisher: Frontiers Research Foundation publist_id: '7078' pubrep_id: '903' quality_controlled: '1' scopus_import: 1 status: public title: Self organized behavior generation for musculoskeletal robots tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2017' ... --- _id: '720' abstract: - lang: eng text: 'Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality.' article_number: e1005763 article_processing_charge: Yes author: - first_name: Jan full_name: Humplik, Jan id: 2E9627A8-F248-11E8-B48F-1D18A9856A87 last_name: Humplik - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Humplik J, Tkačik G. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 2017;13(9). doi:10.1371/journal.pcbi.1005763 apa: Humplik, J., & Tkačik, G. (2017). Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005763 chicago: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” PLoS Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005763. ieee: J. Humplik and G. Tkačik, “Probabilistic models for neural populations that naturally capture global coupling and criticality,” PLoS Computational Biology, vol. 13, no. 9. Public Library of Science, 2017. ista: Humplik J, Tkačik G. 2017. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 13(9), e1005763. mla: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” PLoS Computational Biology, vol. 13, no. 9, e1005763, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005763. short: J. Humplik, G. Tkačik, PLoS Computational Biology 13 (2017). date_created: 2018-12-11T11:48:08Z date_published: 2017-09-19T00:00:00Z date_updated: 2021-01-12T08:12:21Z day: '19' ddc: - '530' - '571' department: - _id: GaTk doi: 10.1371/journal.pcbi.1005763 file: - access_level: open_access checksum: 81107096c19771c36ddbe6f0282a3acb content_type: application/pdf creator: system date_created: 2018-12-12T10:18:30Z date_updated: 2020-07-14T12:47:53Z file_id: '5352' file_name: IST-2017-884-v1+1_journal.pcbi.1005763.pdf file_size: 14167050 relation: main_file file_date_updated: 2020-07-14T12:47:53Z has_accepted_license: '1' intvolume: ' 13' issue: '9' language: - iso: eng month: '09' oa: 1 oa_version: Published Version project: - _id: 255008E4-B435-11E9-9278-68D0E5697425 grant_number: RGP0065/2012 name: Information processing and computation in fish groups - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PLoS Computational Biology publication_identifier: issn: - 1553734X publication_status: published publisher: Public Library of Science publist_id: '6960' pubrep_id: '884' quality_controlled: '1' scopus_import: 1 status: public title: Probabilistic models for neural populations that naturally capture global coupling and criticality tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2017' ... --- _id: '725' abstract: - lang: eng text: Individual computations and social interactions underlying collective behavior in groups of animals are of great ethological, behavioral, and theoretical interest. While complex individual behaviors have successfully been parsed into small dictionaries of stereotyped behavioral modes, studies of collective behavior largely ignored these findings; instead, their focus was on inferring single, mode-independent social interaction rules that reproduced macroscopic and often qualitative features of group behavior. Here, we bring these two approaches together to predict individual swimming patterns of adult zebrafish in a group. We show that fish alternate between an “active” mode, in which they are sensitive to the swimming patterns of conspecifics, and a “passive” mode, where they ignore them. Using a model that accounts for these two modes explicitly, we predict behaviors of individual fish with high accuracy, outperforming previous approaches that assumed a single continuous computation by individuals and simple metric or topological weighing of neighbors’ behavior. At the group level, switching between active and passive modes is uncorrelated among fish, but correlated directional swimming behavior still emerges. Our quantitative approach for studying complex, multi-modal individual behavior jointly with emergent group behavior is readily extensible to additional behavioral modes and their neural correlates as well as to other species. author: - first_name: Roy full_name: Harpaz, Roy last_name: Harpaz - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman citation: ama: Harpaz R, Tkačik G, Schneidman E. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 2017;114(38):10149-10154. doi:10.1073/pnas.1703817114 apa: Harpaz, R., Tkačik, G., & Schneidman, E. (2017). Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1703817114 chicago: Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1703817114. ieee: R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information processing predict individual behavior of fish in a group,” PNAS, vol. 114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017. ista: Harpaz R, Tkačik G, Schneidman E. 2017. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 114(38), 10149–10154. mla: Harpaz, Roy, et al. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS, vol. 114, no. 38, National Academy of Sciences, 2017, pp. 10149–54, doi:10.1073/pnas.1703817114. short: R. Harpaz, G. Tkačik, E. Schneidman, PNAS 114 (2017) 10149–10154. date_created: 2018-12-11T11:48:10Z date_published: 2017-09-19T00:00:00Z date_updated: 2021-01-12T08:12:36Z day: '19' department: - _id: GaTk doi: 10.1073/pnas.1703817114 external_id: pmid: - '28874581' intvolume: ' 114' issue: '38' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617265/ month: '09' oa: 1 oa_version: Submitted Version page: 10149 - 10154 pmid: 1 publication: PNAS publication_identifier: issn: - '00278424' publication_status: published publisher: National Academy of Sciences publist_id: '6953' quality_controlled: '1' scopus_import: 1 status: public title: Discrete modes of social information processing predict individual behavior of fish in a group type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 114 year: '2017' ... --- _id: '9709' abstract: - lang: eng text: Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells’ collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina. article_processing_charge: No author: - first_name: Jason full_name: Prentice, Jason last_name: Prentice - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Mark full_name: Ioffe, Mark last_name: Ioffe - first_name: Adrianna full_name: Loback, Adrianna last_name: Loback - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Michael full_name: Berry, Michael last_name: Berry citation: ama: 'Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. Data from: Error-robust modes of the retinal population code. 2017. doi:10.5061/dryad.1f1rc' apa: 'Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M. (2017). Data from: Error-robust modes of the retinal population code. Dryad. https://doi.org/10.5061/dryad.1f1rc' chicago: 'Prentice, Jason, Olivier Marre, Mark Ioffe, Adrianna Loback, Gašper Tkačik, and Michael Berry. “Data from: Error-Robust Modes of the Retinal Population Code.” Dryad, 2017. https://doi.org/10.5061/dryad.1f1rc.' ieee: 'J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, and M. Berry, “Data from: Error-robust modes of the retinal population code.” Dryad, 2017.' ista: 'Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. 2017. Data from: Error-robust modes of the retinal population code, Dryad, 10.5061/dryad.1f1rc.' mla: 'Prentice, Jason, et al. Data from: Error-Robust Modes of the Retinal Population Code. Dryad, 2017, doi:10.5061/dryad.1f1rc.' short: J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, M. Berry, (2017). date_created: 2021-07-23T11:34:34Z date_published: 2017-10-18T00:00:00Z date_updated: 2023-02-21T16:34:41Z day: '18' department: - _id: GaTk doi: 10.5061/dryad.1f1rc main_file_link: - open_access: '1' url: https://doi.org/10.5061/dryad.1f1rc month: '10' oa: 1 oa_version: Published Version publisher: Dryad related_material: record: - id: '1197' relation: used_in_publication status: public status: public title: 'Data from: Error-robust modes of the retinal population code' type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '680' abstract: - lang: eng text: In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround suppression. Paradoxically, these highly variable receptive fields go alongside and are in fact required for an invariant representation of external sensory features. In addition to offering a normative account of context-dependent changes in sensory responses, perceptual inference in the presence of signal-dependent noise accounts for ubiquitous features of sensory neurons such as divisive normalization, gain control and contrast dependent temporal dynamics. article_number: e1005582 author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Paul full_name: Masset, Paul last_name: Masset - first_name: Boris full_name: Gutkin, Boris last_name: Gutkin - first_name: Sophie full_name: Denève, Sophie last_name: Denève citation: ama: Chalk MJ, Masset P, Gutkin B, Denève S. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 2017;13(6). doi:10.1371/journal.pcbi.1005582 apa: Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582 chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582. ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts divisive reshaping of receptive fields,” PLoS Computational Biology, vol. 13, no. 6. Public Library of Science, 2017. ista: Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 13(6), e1005582. mla: Chalk, Matthew J., et al. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational Biology, vol. 13, no. 6, e1005582, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005582. short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, PLoS Computational Biology 13 (2017). date_created: 2018-12-11T11:47:53Z date_published: 2017-06-01T00:00:00Z date_updated: 2023-02-23T14:10:54Z day: '01' ddc: - '571' department: - _id: GaTk doi: 10.1371/journal.pcbi.1005582 file: - access_level: open_access checksum: 796a1026076af6f4405a47d985bc7b68 content_type: application/pdf creator: system date_created: 2018-12-12T10:07:47Z date_updated: 2020-07-14T12:47:40Z file_id: '4645' file_name: IST-2017-898-v1+1_journal.pcbi.1005582.pdf file_size: 14555676 relation: main_file file_date_updated: 2020-07-14T12:47:40Z has_accepted_license: '1' intvolume: ' 13' issue: '6' language: - iso: eng month: '06' oa: 1 oa_version: Published Version publication: PLoS Computational Biology publication_identifier: issn: - 1553734X publication_status: published publisher: Public Library of Science publist_id: '7035' pubrep_id: '898' quality_controlled: '1' related_material: record: - id: '9855' relation: research_data status: public scopus_import: 1 status: public title: Sensory noise predicts divisive reshaping of receptive fields tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2017' ... --- _id: '9855' abstract: - lang: eng text: Includes derivation of optimal estimation algorithm, generalisation to non-poisson noise statistics, correlated input noise, and implementation of in a multi-layer neural network. article_processing_charge: No author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Paul full_name: Masset, Paul last_name: Masset - first_name: Boris full_name: Gutkin, Boris last_name: Gutkin - first_name: Sophie full_name: Denève, Sophie last_name: Denève citation: ama: Chalk MJ, Masset P, Gutkin B, Denève S. Supplementary appendix. 2017. doi:10.1371/journal.pcbi.1005582.s001 apa: Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Supplementary appendix. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582.s001 chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Supplementary Appendix.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582.s001. ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Supplementary appendix.” Public Library of Science, 2017. ista: Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Supplementary appendix, Public Library of Science, 10.1371/journal.pcbi.1005582.s001. mla: Chalk, Matthew J., et al. Supplementary Appendix. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005582.s001. short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, (2017). date_created: 2021-08-10T07:05:10Z date_published: 2017-06-01T00:00:00Z date_updated: 2023-02-23T12:52:17Z day: '01' department: - _id: GaTk doi: 10.1371/journal.pcbi.1005582.s001 month: '06' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '680' relation: used_in_publication status: public status: public title: Supplementary appendix type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '666' abstract: - lang: eng text: Antibiotics elicit drastic changes in microbial gene expression, including the induction of stress response genes. While certain stress responses are known to “cross-protect” bacteria from other stressors, it is unclear whether cellular responses to antibiotics have a similar protective role. By measuring the genome-wide transcriptional response dynamics of Escherichia coli to four antibiotics, we found that trimethoprim induces a rapid acid stress response that protects bacteria from subsequent exposure to acid. Combining microfluidics with time-lapse imaging to monitor survival and acid stress response in single cells revealed that the noisy expression of the acid resistance operon gadBC correlates with single-cell survival. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. The seemingly random single-cell survival under acid stress can therefore be predicted from gadBC expression and rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap for identifying the molecular mechanisms of single-cell cross-protection between antibiotics and other stressors. article_processing_charge: Yes (in subscription journal) author: - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001 apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2017). Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001 chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems. Cell Press, 2017. https://doi.org/10.1016/j.cels.2017.03.001. ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment,” Cell Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017. ista: Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 4(4), 393–403. mla: Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no. 4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001. short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403. date_created: 2018-12-11T11:47:48Z date_published: 2017-04-26T00:00:00Z date_updated: 2023-09-07T12:00:25Z day: '26' ddc: - '576' - '610' department: - _id: ToBo - _id: GaTk doi: 10.1016/j.cels.2017.03.001 ec_funded: 1 file: - access_level: open_access checksum: 04ff20011c3d9a601c514aa999a5fe1a content_type: application/pdf creator: system date_created: 2018-12-12T10:13:54Z date_updated: 2020-07-14T12:47:35Z file_id: '5041' file_name: IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf file_size: 2438660 relation: main_file file_date_updated: 2020-07-14T12:47:35Z has_accepted_license: '1' intvolume: ' 4' issue: '4' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '04' oa: 1 oa_version: Published Version page: 393 - 403 project: - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Cell Systems publication_identifier: issn: - '24054712' publication_status: published publisher: Cell Press publist_id: '7061' pubrep_id: '901' quality_controlled: '1' related_material: record: - id: '818' relation: dissertation_contains status: public scopus_import: 1 status: public title: Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2017' ... --- _id: '2016' abstract: - lang: eng text: The Ising model is one of the simplest and most famous models of interacting systems. It was originally proposed to model ferromagnetic interactions in statistical physics and is now widely used to model spatial processes in many areas such as ecology, sociology, and genetics, usually without testing its goodness-of-fit. Here, we propose an exact goodness-of-fit test for the finite-lattice Ising model. The theory of Markov bases has been developed in algebraic statistics for exact goodness-of-fit testing using a Monte Carlo approach. However, this beautiful theory has fallen short of its promise for applications, because finding a Markov basis is usually computationally intractable. We develop a Monte Carlo method for exact goodness-of-fit testing for the Ising model which avoids computing a Markov basis and also leads to a better connectivity of the Markov chain and hence to a faster convergence. We show how this method can be applied to analyze the spatial organization of receptors on the cell membrane. article_processing_charge: No author: - first_name: Abraham full_name: Martin Del Campo Sanchez, Abraham last_name: Martin Del Campo Sanchez - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Caroline full_name: Uhler, Caroline id: 49ADD78E-F248-11E8-B48F-1D18A9856A87 last_name: Uhler orcid: 0000-0002-7008-0216 citation: ama: Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 2017;44(2):285-306. doi:10.1111/sjos.12251 apa: Martin Del Campo Sanchez, A., Cepeda Humerez, S. A., & Uhler, C. (2017). Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. Wiley-Blackwell. https://doi.org/10.1111/sjos.12251 chicago: Martin Del Campo Sanchez, Abraham, Sarah A Cepeda Humerez, and Caroline Uhler. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal of Statistics. Wiley-Blackwell, 2017. https://doi.org/10.1111/sjos.12251. ieee: A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit testing for the Ising model,” Scandinavian Journal of Statistics, vol. 44, no. 2. Wiley-Blackwell, pp. 285–306, 2017. ista: Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. 2017. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 44(2), 285–306. mla: Martin Del Campo Sanchez, Abraham, et al. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal of Statistics, vol. 44, no. 2, Wiley-Blackwell, 2017, pp. 285–306, doi:10.1111/sjos.12251. short: A. Martin Del Campo Sanchez, S.A. Cepeda Humerez, C. Uhler, Scandinavian Journal of Statistics 44 (2017) 285–306. date_created: 2018-12-11T11:55:13Z date_published: 2017-06-01T00:00:00Z date_updated: 2023-09-19T15:13:27Z day: '01' department: - _id: GaTk doi: 10.1111/sjos.12251 external_id: arxiv: - '1410.1242' isi: - '000400985000001' intvolume: ' 44' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1410.1242 month: '06' oa: 1 oa_version: Preprint page: 285 - 306 publication: Scandinavian Journal of Statistics publication_identifier: issn: - '03036898' publication_status: published publisher: Wiley-Blackwell publist_id: '5060' quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: '1' status: public title: Exact goodness-of-fit testing for the Ising model type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 44 year: '2017' ... --- _id: '1104' abstract: - lang: eng text: In the early visual system, cells of the same type perform the same computation in different places of the visual field. How these cells code together a complex visual scene is unclear. A common assumption is that cells of a single-type extract a single-stimulus feature to form a feature map, but this has rarely been observed directly. Using large-scale recordings in the rat retina, we show that a homogeneous population of fast OFF ganglion cells simultaneously encodes two radically different features of a visual scene. Cells close to a moving object code quasilinearly for its position, while distant cells remain largely invariant to the object's position and, instead, respond nonlinearly to changes in the object's speed. We develop a quantitative model that accounts for this effect and identify a disinhibitory circuit that mediates it. Ganglion cells of a single type thus do not code for one, but two features simultaneously. This richer, flexible neural map might also be present in other sensory systems. article_number: '1964' article_processing_charge: No author: - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Ulisse full_name: Ferrari, Ulisse last_name: Ferrari - first_name: Emilie full_name: Mace, Emilie last_name: Mace - first_name: Pierre full_name: Yger, Pierre last_name: Yger - first_name: Romain full_name: Caplette, Romain last_name: Caplette - first_name: Serge full_name: Picaud, Serge last_name: Picaud - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre citation: ama: Deny S, Ferrari U, Mace E, et al. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-02159-y apa: Deny, S., Ferrari, U., Mace, E., Yger, P., Caplette, R., Picaud, S., … Marre, O. (2017). Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-02159-y chicago: Deny, Stephane, Ulisse Ferrari, Emilie Mace, Pierre Yger, Romain Caplette, Serge Picaud, Gašper Tkačik, and Olivier Marre. “Multiplexed Computations in Retinal Ganglion Cells of a Single Type.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-02159-y. ieee: S. Deny et al., “Multiplexed computations in retinal ganglion cells of a single type,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017. ista: Deny S, Ferrari U, Mace E, Yger P, Caplette R, Picaud S, Tkačik G, Marre O. 2017. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 8(1), 1964. mla: Deny, Stephane, et al. “Multiplexed Computations in Retinal Ganglion Cells of a Single Type.” Nature Communications, vol. 8, no. 1, 1964, Nature Publishing Group, 2017, doi:10.1038/s41467-017-02159-y. short: S. Deny, U. Ferrari, E. Mace, P. Yger, R. Caplette, S. Picaud, G. Tkačik, O. Marre, Nature Communications 8 (2017). date_created: 2018-12-11T11:50:10Z date_published: 2017-12-06T00:00:00Z date_updated: 2023-09-20T11:41:19Z day: '06' ddc: - '571' department: - _id: GaTk doi: 10.1038/s41467-017-02159-y ec_funded: 1 external_id: isi: - '000417241200004' file: - access_level: open_access content_type: application/pdf creator: system date_created: 2018-12-12T10:16:06Z date_updated: 2018-12-12T10:16:06Z file_id: '5191' file_name: IST-2018-921-v1+1_s41467-017-02159-y.pdf file_size: 2872887 relation: main_file file_date_updated: 2018-12-12T10:16:06Z has_accepted_license: '1' intvolume: ' 8' isi: 1 issue: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 25CD3DD2-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '604102' name: Localization of ion channels and receptors by two and three-dimensional immunoelectron microscopic approaches - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '6266' pubrep_id: '921' quality_controlled: '1' scopus_import: '1' status: public title: Multiplexed computations in retinal ganglion cells of a single type tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 8 year: '2017' ... --- _id: '993' abstract: - lang: eng text: In real-world applications, observations are often constrained to a small fraction of a system. Such spatial subsampling can be caused by the inaccessibility or the sheer size of the system, and cannot be overcome by longer sampling. Spatial subsampling can strongly bias inferences about a system’s aggregated properties. To overcome the bias, we derive analytically a subsampling scaling framework that is applicable to different observables, including distributions of neuronal avalanches, of number of people infected during an epidemic outbreak, and of node degrees. We demonstrate how to infer the correct distributions of the underlying full system, how to apply it to distinguish critical from subcritical systems, and how to disentangle subsampling and finite size effects. Lastly, we apply subsampling scaling to neuronal avalanche models and to recordings from developing neural networks. We show that only mature, but not young networks follow power-law scaling, indicating self-organization to criticality during development. article_number: '15140' article_processing_charge: Yes (in subscription journal) author: - first_name: Anna full_name: Levina (Martius), Anna id: 35AF8020-F248-11E8-B48F-1D18A9856A87 last_name: Levina (Martius) - first_name: Viola full_name: Priesemann, Viola last_name: Priesemann citation: ama: Levina (Martius) A, Priesemann V. Subsampling scaling. Nature Communications. 2017;8. doi:10.1038/ncomms15140 apa: Levina (Martius), A., & Priesemann, V. (2017). Subsampling scaling. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms15140 chicago: Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/ncomms15140. ieee: A. Levina (Martius) and V. Priesemann, “Subsampling scaling,” Nature Communications, vol. 8. Nature Publishing Group, 2017. ista: Levina (Martius) A, Priesemann V. 2017. Subsampling scaling. Nature Communications. 8, 15140. mla: Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature Communications, vol. 8, 15140, Nature Publishing Group, 2017, doi:10.1038/ncomms15140. short: A. Levina (Martius), V. Priesemann, Nature Communications 8 (2017). date_created: 2018-12-11T11:49:35Z date_published: 2017-05-04T00:00:00Z date_updated: 2023-09-22T09:54:07Z day: '04' ddc: - '005' - '571' department: - _id: GaTk - _id: JoCs doi: 10.1038/ncomms15140 ec_funded: 1 external_id: isi: - '000400560700001' file: - access_level: open_access checksum: 9880212f8c4c53404c7c6fbf9023c53a content_type: application/pdf creator: system date_created: 2018-12-12T10:15:05Z date_updated: 2020-07-14T12:48:19Z file_id: '5122' file_name: IST-2017-819-v1+1_2017_Levina_SubsamplingScaling.pdf file_size: 746224 relation: main_file file_date_updated: 2020-07-14T12:48:19Z has_accepted_license: '1' intvolume: ' 8' isi: 1 language: - iso: eng month: '05' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '6406' pubrep_id: '819' quality_controlled: '1' scopus_import: '1' status: public title: Subsampling scaling tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 8 year: '2017' ... --- _id: '955' abstract: - lang: eng text: 'Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components.' article_number: '216' article_processing_charge: Yes (in subscription journal) author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Friedlander T, Prizak R, Barton NH, Tkačik G. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-00238-8 apa: Friedlander, T., Prizak, R., Barton, N. H., & Tkačik, G. (2017). Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-00238-8 chicago: Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-00238-8. ieee: T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new regulatory functions on biophysically realistic fitness landscapes,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017. ista: Friedlander T, Prizak R, Barton NH, Tkačik G. 2017. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 8(1), 216. mla: Friedlander, Tamar, et al. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications, vol. 8, no. 1, 216, Nature Publishing Group, 2017, doi:10.1038/s41467-017-00238-8. short: T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications 8 (2017). date_created: 2018-12-11T11:49:23Z date_published: 2017-08-09T00:00:00Z date_updated: 2023-09-22T10:00:49Z day: '09' ddc: - '539' - '576' department: - _id: GaTk - _id: NiBa doi: 10.1038/s41467-017-00238-8 ec_funded: 1 external_id: isi: - '000407198800005' file: - access_level: open_access checksum: 29a1b5db458048d3bd5c67e0e2a56818 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:14Z date_updated: 2020-07-14T12:48:16Z file_id: '5064' file_name: IST-2017-864-v1+1_s41467-017-00238-8.pdf file_size: 998157 relation: main_file - access_level: open_access checksum: 7b78401e52a576cf3e6bbf8d0abadc17 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:15Z date_updated: 2020-07-14T12:48:16Z file_id: '5065' file_name: IST-2017-864-v1+2_41467_2017_238_MOESM1_ESM.pdf file_size: 9715993 relation: main_file file_date_updated: 2020-07-14T12:48:16Z has_accepted_license: '1' intvolume: ' 8' isi: 1 issue: '1' language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '6459' pubrep_id: '864' quality_controlled: '1' related_material: record: - id: '6071' relation: dissertation_contains status: public scopus_import: '1' status: public title: Evolution of new regulatory functions on biophysically realistic fitness landscapes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 8 year: '2017' ... --- _id: '959' abstract: - lang: eng text: In this work it is shown that scale-free tails in metabolic flux distributions inferred in stationary models are an artifact due to reactions involved in thermodynamically unfeasible cycles, unbounded by physical constraints and in principle able to perform work without expenditure of free energy. After implementing thermodynamic constraints by removing such loops, metabolic flux distributions scale meaningfully with the physical limiting factors, acquiring in turn a richer multimodal structure potentially leading to symmetry breaking while optimizing for objective functions. article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: De Martino D. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;95(6):062419. doi:10.1103/PhysRevE.95.062419 apa: De Martino, D. (2017). Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.95.062419 chicago: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.95.062419. ieee: D. De Martino, “Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics,” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 95, no. 6. American Institute of Physics, p. 062419, 2017. ista: De Martino D. 2017. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 95(6), 062419. mla: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 95, no. 6, American Institute of Physics, 2017, p. 062419, doi:10.1103/PhysRevE.95.062419. short: D. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 95 (2017) 062419. date_created: 2018-12-11T11:49:25Z date_published: 2017-06-28T00:00:00Z date_updated: 2023-09-22T09:59:01Z day: '28' department: - _id: GaTk doi: 10.1103/PhysRevE.95.062419 ec_funded: 1 external_id: isi: - '000404546400004' intvolume: ' 95' isi: 1 issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/pdf/1703.00853.pdf month: '06' oa: 1 oa_version: Submitted Version page: '062419' project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics ' publication_identifier: issn: - '24700045' publication_status: published publisher: American Institute of Physics publist_id: '6446' quality_controlled: '1' scopus_import: '1' status: public title: Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 95 year: '2017' ... --- _id: '947' abstract: - lang: eng text: Viewing the ways a living cell can organize its metabolism as the phase space of a physical system, regulation can be seen as the ability to reduce the entropy of that space by selecting specific cellular configurations that are, in some sense, optimal. Here we quantify the amount of regulation required to control a cell's growth rate by a maximum-entropy approach to the space of underlying metabolic phenotypes, where a configuration corresponds to a metabolic flux pattern as described by genome-scale models. We link the mean growth rate achieved by a population of cells to the minimal amount of metabolic regulation needed to achieve it through a phase diagram that highlights how growth suppression can be as costly (in regulatory terms) as growth enhancement. Moreover, we provide an interpretation of the inverse temperature β controlling maximum-entropy distributions based on the underlying growth dynamics. Specifically, we show that the asymptotic value of β for a cell population can be expected to depend on (i) the carrying capacity of the environment, (ii) the initial size of the colony, and (iii) the probability distribution from which the inoculum was sampled. Results obtained for E. coli and human cells are found to be remarkably consistent with empirical evidence. article_number: '010401' article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Fabrizio full_name: Capuani, Fabrizio last_name: Capuani - first_name: Andrea full_name: De Martino, Andrea last_name: De Martino citation: ama: De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;96(1). doi:10.1103/PhysRevE.96.010401 apa: De Martino, D., Capuani, F., & De Martino, A. (2017). Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401 chicago: De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401. ieee: D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost of cellular growth control,” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1. American Institute of Physics, 2017. ista: De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401. mla: De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:10.1103/PhysRevE.96.010401. short: D. De Martino, F. Capuani, A. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 96 (2017). date_created: 2018-12-11T11:49:21Z date_published: 2017-07-10T00:00:00Z date_updated: 2023-09-22T10:03:50Z day: '10' department: - _id: GaTk doi: 10.1103/PhysRevE.96.010401 ec_funded: 1 external_id: isi: - '000405194200002' intvolume: ' 96' isi: 1 issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1703.00219 month: '07' oa: 1 oa_version: Submitted Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics ' publication_identifier: issn: - '24700045' publication_status: published publisher: American Institute of Physics publist_id: '6470' quality_controlled: '1' scopus_import: '1' status: public title: Quantifying the entropic cost of cellular growth control type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 96 year: '2017' ... --- _id: '943' abstract: - lang: eng text: Like many developing tissues, the vertebrate neural tube is patterned by antiparallel morphogen gradients. To understand how these inputs are interpreted, we measured morphogen signaling and target gene expression in mouse embryos and chick ex vivo assays. From these data, we derived and validated a characteristic decoding map that relates morphogen input to the positional identity of neural progenitors. Analysis of the observed responses indicates that the underlying interpretation strategy minimizes patterning errors in response to the joint input of noisy opposing gradients. We reverse-engineered a transcriptional network that provides a mechanistic basis for the observed cell fate decisions and accounts for the precision and dynamics of pattern formation. Together, our data link opposing gradient dynamics in a growing tissue to precise pattern formation. article_processing_charge: No author: - first_name: Marcin P full_name: Zagórski, Marcin P id: 343DA0DC-F248-11E8-B48F-1D18A9856A87 last_name: Zagórski orcid: 0000-0001-7896-7762 - first_name: Yoji full_name: Tabata, Yoji last_name: Tabata - first_name: Nathalie full_name: Brandenberg, Nathalie last_name: Brandenberg - first_name: Matthias full_name: Lutolf, Matthias last_name: Lutolf - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Tobias full_name: Bollenbach, Tobias last_name: Bollenbach - first_name: James full_name: Briscoe, James last_name: Briscoe - first_name: Anna full_name: Kicheva, Anna id: 3959A2A0-F248-11E8-B48F-1D18A9856A87 last_name: Kicheva orcid: 0000-0003-4509-4998 citation: ama: Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383. doi:10.1126/science.aam5887 apa: Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach, T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aam5887 chicago: Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf, Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aam5887. ieee: M. P. Zagórski et al., “Decoding of position in the developing neural tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345. American Association for the Advancement of Science, pp. 1379–1383, 2017. ista: Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 356(6345), 1379–1383. mla: Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” Science, vol. 356, no. 6345, American Association for the Advancement of Science, 2017, pp. 1379–83, doi:10.1126/science.aam5887. short: M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach, J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383. date_created: 2018-12-11T11:49:20Z date_published: 2017-06-30T00:00:00Z date_updated: 2023-09-26T15:38:05Z day: '30' department: - _id: AnKi - _id: GaTk doi: 10.1126/science.aam5887 ec_funded: 1 external_id: isi: - '000404351500036' pmid: - '28663499' intvolume: ' 356' isi: 1 issue: '6345' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/ month: '06' oa: 1 oa_version: Submitted Version page: 1379 - 1383 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation - _id: B6FC0238-B512-11E9-945C-1524E6697425 call_identifier: H2020 grant_number: '680037' name: Coordination of Patterning And Growth In the Spinal Cord - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2524F500-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '201439' name: Developing High-Throughput Bioassays for Human Cancers in Zebrafish publication: Science publication_identifier: issn: - '00368075' publication_status: published publisher: American Association for the Advancement of Science publist_id: '6474' quality_controlled: '1' scopus_import: '1' status: public title: Decoding of position in the developing neural tube from antiparallel morphogen gradients type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 356 year: '2017' ... --- _id: '823' abstract: - lang: eng text: The resolution of a linear system with positive integer variables is a basic yet difficult computational problem with many applications. We consider sparse uncorrelated random systems parametrised by the density c and the ratio α=N/M between number of variables N and number of constraints M. By means of ensemble calculations we show that the space of feasible solutions endows a Van-Der-Waals phase diagram in the plane (c, α). We give numerical evidence that the associated computational problems become more difficult across the critical point and in particular in the coexistence region. article_number: '093404' article_processing_charge: No author: - first_name: Simona full_name: Colabrese, Simona last_name: Colabrese - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Luca full_name: Leuzzi, Luca last_name: Leuzzi - first_name: Enzo full_name: Marinari, Enzo last_name: Marinari citation: ama: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. 2017;2017(9). doi:10.1088/1742-5468/aa85c3' apa: 'Colabrese, S., De Martino, D., Leuzzi, L., & Marinari, E. (2017). Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa85c3' chicago: 'Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2017. https://doi.org/10.1088/1742-5468/aa85c3.' ieee: 'S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions in integer linear problems,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9. IOPscience, 2017.' ista: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. 2017. Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. 2017(9), 093404.' mla: 'Colabrese, Simona, et al. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9, 093404, IOPscience, 2017, doi:10.1088/1742-5468/aa85c3.' short: 'S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari, Journal of Statistical Mechanics: Theory and Experiment 2017 (2017).' date_created: 2018-12-11T11:48:41Z date_published: 2017-09-26T00:00:00Z date_updated: 2023-09-26T16:18:12Z day: '26' department: - _id: GaTk doi: 10.1088/1742-5468/aa85c3 ec_funded: 1 external_id: isi: - '000411842900001' intvolume: ' 2017' isi: 1 issue: '9' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1705.06303 month: '09' oa: 1 oa_version: Submitted Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Journal of Statistical Mechanics: Theory and Experiment' publication_identifier: issn: - '17425468' publication_status: published publisher: IOPscience publist_id: '6826' quality_controlled: '1' scopus_import: '1' status: public title: Phase transitions in integer linear problems type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2017 year: '2017' ... --- _id: '730' abstract: - lang: eng text: Neural responses are highly structured, with population activity restricted to a small subset of the astronomical range of possible activity patterns. Characterizing these statistical regularities is important for understanding circuit computation, but challenging in practice. Here we review recent approaches based on the maximum entropy principle used for quantifying collective behavior in neural activity. We highlight recent models that capture population-level statistics of neural data, yielding insights into the organization of the neural code and its biological substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing surrogate ensembles that preserve aspects of the data, but are otherwise maximally unstructured. This idea can be used to generate a hierarchy of controls against which rigorous statistical tests are possible. article_processing_charge: No author: - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Savin C, Tkačik G. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 2017;46:120-126. doi:10.1016/j.conb.2017.08.001 apa: Savin, C., & Tkačik, G. (2017). Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. Elsevier. https://doi.org/10.1016/j.conb.2017.08.001 chicago: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” Current Opinion in Neurobiology. Elsevier, 2017. https://doi.org/10.1016/j.conb.2017.08.001. ieee: C. Savin and G. Tkačik, “Maximum entropy models as a tool for building precise neural controls,” Current Opinion in Neurobiology, vol. 46. Elsevier, pp. 120–126, 2017. ista: Savin C, Tkačik G. 2017. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 46, 120–126. mla: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” Current Opinion in Neurobiology, vol. 46, Elsevier, 2017, pp. 120–26, doi:10.1016/j.conb.2017.08.001. short: C. Savin, G. Tkačik, Current Opinion in Neurobiology 46 (2017) 120–126. date_created: 2018-12-11T11:48:11Z date_published: 2017-10-01T00:00:00Z date_updated: 2023-09-28T11:32:22Z day: '01' department: - _id: GaTk doi: 10.1016/j.conb.2017.08.001 ec_funded: 1 external_id: isi: - '000416196400016' intvolume: ' 46' isi: 1 language: - iso: eng month: '10' oa_version: None page: 120 - 126 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Current Opinion in Neurobiology publication_identifier: issn: - '09594388' publication_status: published publisher: Elsevier publist_id: '6943' quality_controlled: '1' scopus_import: '1' status: public title: Maximum entropy models as a tool for building precise neural controls type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 46 year: '2017' ... --- _id: '548' abstract: - lang: eng text: In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region. alternative_title: - Rapid Communications article_number: '060401' article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: De Martino D. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 2017;96(6). doi:10.1103/PhysRevE.96.060401 apa: De Martino, D. (2017). Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.96.060401 chicago: De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E. American Physical Society, 2017. https://doi.org/10.1103/PhysRevE.96.060401. ieee: D. De Martino, “Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes,” Physical Review E, vol. 96, no. 6. American Physical Society, 2017. ista: De Martino D. 2017. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 96(6), 060401. mla: De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E, vol. 96, no. 6, 060401, American Physical Society, 2017, doi:10.1103/PhysRevE.96.060401. short: D. De Martino, Physical Review E 96 (2017). date_created: 2018-12-11T11:47:06Z date_published: 2017-12-21T00:00:00Z date_updated: 2023-10-10T13:29:38Z day: '21' department: - _id: GaTk doi: 10.1103/PhysRevE.96.060401 ec_funded: 1 intvolume: ' 96' issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1707.00320 month: '12' oa: 1 oa_version: Submitted Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Physical Review E publication_identifier: issn: - 2470-0045 publication_status: published publisher: American Physical Society publist_id: '7266' quality_controlled: '1' scopus_import: '1' status: public title: Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 96 year: '2017' ... --- _id: '1007' abstract: - lang: eng text: 'A nonlinear system possesses an invariance with respect to a set of transformations if its output dynamics remain invariant when transforming the input, and adjusting the initial condition accordingly. Most research has focused on invariances with respect to time-independent pointwise transformations like translational-invariance (u(t) -> u(t) + p, p in R) or scale-invariance (u(t) -> pu(t), p in R>0). In this article, we introduce the concept of s0-invariances with respect to continuous input transformations exponentially growing/decaying over time. We show that s0-invariant systems not only encompass linear time-invariant (LTI) systems with transfer functions having an irreducible zero at s0 in R, but also that the input/output relationship of nonlinear s0-invariant systems possesses properties well known from their linear counterparts. Furthermore, we extend the concept of s0-invariances to second- and higher-order s0-invariances, corresponding to invariances with respect to transformations of the time-derivatives of the input, and encompassing LTI systems with zeros of multiplicity two or higher. Finally, we show that nth-order 0-invariant systems realize – under mild conditions – nth-order nonlinear differential operators: when excited by an input of a characteristic functional form, the system’s output converges to a constant value only depending on the nth (nonlinear) derivative of the input.' article_processing_charge: Yes (in subscription journal) author: - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Eduardo full_name: Sontag, Eduardo last_name: Sontag citation: ama: Lang M, Sontag E. Zeros of nonlinear systems with input invariances. Automatica. 2017;81C:46-55. doi:10.1016/j.automatica.2017.03.030 apa: Lang, M., & Sontag, E. (2017). Zeros of nonlinear systems with input invariances. Automatica. International Federation of Automatic Control. https://doi.org/10.1016/j.automatica.2017.03.030 chicago: Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input Invariances.” Automatica. International Federation of Automatic Control, 2017. https://doi.org/10.1016/j.automatica.2017.03.030. ieee: M. Lang and E. Sontag, “Zeros of nonlinear systems with input invariances,” Automatica, vol. 81C. International Federation of Automatic Control, pp. 46–55, 2017. ista: Lang M, Sontag E. 2017. Zeros of nonlinear systems with input invariances. Automatica. 81C, 46–55. mla: Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input Invariances.” Automatica, vol. 81C, International Federation of Automatic Control, 2017, pp. 46–55, doi:10.1016/j.automatica.2017.03.030. short: M. Lang, E. Sontag, Automatica 81C (2017) 46–55. date_created: 2018-12-11T11:49:39Z date_published: 2017-06-01T00:00:00Z date_updated: 2023-10-17T08:51:18Z day: '01' ddc: - '000' department: - _id: CaGu - _id: GaTk doi: 10.1016/j.automatica.2017.03.030 ec_funded: 1 external_id: isi: - '000403513900006' file: - access_level: open_access content_type: application/pdf creator: system date_created: 2018-12-12T10:11:29Z date_updated: 2018-12-12T10:11:29Z file_id: '4884' file_name: IST-2017-813-v1+1_ZerosOfNonlinearSystems.pdf file_size: 1401954 relation: main_file file_date_updated: 2018-12-12T10:11:29Z has_accepted_license: '1' isi: 1 language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: 46 - 55 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Automatica publication_identifier: issn: - 0005-1098 publication_status: published publisher: International Federation of Automatic Control publist_id: '6391' pubrep_id: '813' quality_controlled: '1' scopus_import: '1' status: public title: Zeros of nonlinear systems with input invariances tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 81C year: '2017' ... --- _id: '5562' abstract: - lang: eng text: "This data was collected as part of the study [1]. It consists of preprocessed multi-electrode array recording from 160 salamander retinal ganglion cells responding to 297 repeats of a 19 s natural movie. The data is available in two formats: (1) a .mat file containing an array with dimensions “number of repeats” x “number of neurons” x “time in a repeat”; (2) a zipped .txt file containing the same data represented as an array with dimensions “number of neurons” x “number of samples”, where the number of samples is equal to the product of the number of repeats and timebins within a repeat. The time dimension is divided into 20 ms time windows, and the array is binary indicating whether a given cell elicited at least one spike in a given time window during a particular repeat. See the reference below for details regarding collection and preprocessing:\r\n\r\n[1] Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry MJ II. Searching for Collective Behavior in a Large Network of Sensory Neurons. PLoS Comput Biol. 2014;10(1):e1003408." article_processing_charge: No author: - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Dario full_name: Amodei, Dario last_name: Amodei - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman - first_name: William full_name: Bialek, William last_name: Bialek - first_name: Michael full_name: Berry, Michael last_name: Berry citation: ama: Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. Multi-electrode array recording from salamander retinal ganglion cells. 2017. doi:10.15479/AT:ISTA:61 apa: Marre, O., Tkačik, G., Amodei, D., Schneidman, E., Bialek, W., & Berry, M. (2017). Multi-electrode array recording from salamander retinal ganglion cells. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:61 chicago: Marre, Olivier, Gašper Tkačik, Dario Amodei, Elad Schneidman, William Bialek, and Michael Berry. “Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:61. ieee: O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Multi-electrode array recording from salamander retinal ganglion cells.” Institute of Science and Technology Austria, 2017. ista: Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. 2017. Multi-electrode array recording from salamander retinal ganglion cells, Institute of Science and Technology Austria, 10.15479/AT:ISTA:61. mla: Marre, Olivier, et al. Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:61. short: O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, M. Berry, (2017). datarep_id: '61' date_created: 2018-12-12T12:31:33Z date_published: 2017-02-27T00:00:00Z date_updated: 2024-02-21T13:46:14Z day: '27' ddc: - '570' department: - _id: GaTk doi: 10.15479/AT:ISTA:61 file: - access_level: open_access checksum: e620eff260646f57b479a69492c8b765 content_type: application/octet-stream creator: system date_created: 2018-12-12T13:03:04Z date_updated: 2020-07-14T12:47:03Z file_id: '5622' file_name: IST-2017-61-v1+1_bint_fishmovie32_100.mat file_size: 1336936 relation: main_file - access_level: open_access checksum: de83f9b81ea0aae3cddfc3ed982e0759 content_type: application/zip creator: system date_created: 2018-12-12T13:03:05Z date_updated: 2020-07-14T12:47:03Z file_id: '5623' file_name: IST-2017-61-v1+2_bint_fishmovie32_100.zip file_size: 1897543 relation: main_file file_date_updated: 2020-07-14T12:47:03Z has_accepted_license: '1' keyword: - multi-electrode recording - retinal ganglion cells month: '02' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria related_material: record: - id: '2257' relation: research_paper status: public status: public title: Multi-electrode array recording from salamander retinal ganglion cells tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2017' ... --- _id: '5560' abstract: - lang: eng text: "This repository contains the data collected for the manuscript \"Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity\".\r\nThe data is compressed into a single archive. Within the archive, different folders correspond to figures of the main text and the SI of the related publication.\r\nData is saved as plain text, with each folder containing a separate readme file describing the format. Typically, the data is from fluorescence microscopy measurements of single cells growing in a microfluidic \"mother machine\" device, and consists of relevant values (primarily arbitrary unit or normalized fluorescence measurements, and division times / growth rates) after raw microscopy images have been processed, segmented, and their features extracted, as described in the methods section of the related publication." article_processing_charge: No author: - first_name: Tobias full_name: Bergmiller, Tobias id: 2C471CFA-F248-11E8-B48F-1D18A9856A87 last_name: Bergmiller orcid: 0000-0001-5396-4346 - first_name: Anna M full_name: Andersson, Anna M id: 2B8A40DA-F248-11E8-B48F-1D18A9856A87 last_name: Andersson orcid: 0000-0003-2912-6769 - first_name: Kathrin full_name: Tomasek, Kathrin id: 3AEC8556-F248-11E8-B48F-1D18A9856A87 last_name: Tomasek orcid: 0000-0003-3768-877X - first_name: Enrique full_name: Balleza, Enrique last_name: Balleza - first_name: Daniel full_name: Kiviet, Daniel last_name: Kiviet - first_name: Robert full_name: Hauschild, Robert id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87 last_name: Hauschild orcid: 0000-0001-9843-3522 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. 2017. doi:10.15479/AT:ISTA:53 apa: Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:53 chicago: Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:53. ieee: T. Bergmiller et al., “Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity.” Institute of Science and Technology Austria, 2017. ista: Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik G, Guet CC. 2017. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity, Institute of Science and Technology Austria, 10.15479/AT:ISTA:53. mla: Bergmiller, Tobias, et al. Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:53. short: T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, (2017). datarep_id: '53' date_created: 2018-12-12T12:31:32Z date_published: 2017-03-10T00:00:00Z date_updated: 2024-02-21T13:49:00Z day: '10' ddc: - '571' department: - _id: CaGu - _id: GaTk - _id: Bio doi: 10.15479/AT:ISTA:53 file: - access_level: open_access checksum: d77859af757ac8025c50c7b12b52eaf3 content_type: application/zip creator: system date_created: 2018-12-12T13:02:38Z date_updated: 2020-07-14T12:47:03Z file_id: '5603' file_name: IST-2017-53-v1+1_Data_MDE.zip file_size: 6773204 relation: main_file file_date_updated: 2020-07-14T12:47:03Z has_accepted_license: '1' keyword: - single cell microscopy - mother machine microfluidic device - AcrAB-TolC pump - multi-drug efflux - Escherichia coli month: '03' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria related_material: record: - id: '665' relation: research_paper status: public status: public title: Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2017' ... --- _id: '665' abstract: - lang: eng text: The molecular mechanisms underlying phenotypic variation in isogenic bacterial populations remain poorly understood.We report that AcrAB-TolC, the main multidrug efflux pump of Escherichia coli, exhibits a strong partitioning bias for old cell poles by a segregation mechanism that is mediated by ternary AcrAB-TolC complex formation. Mother cells inheriting old poles are phenotypically distinct and display increased drug efflux activity relative to daughters. Consequently, we find systematic and long-lived growth differences between mother and daughter cells in the presence of subinhibitory drug concentrations. A simple model for biased partitioning predicts a population structure of long-lived and highly heterogeneous phenotypes. This straightforward mechanism of generating sustained growth rate differences at subinhibitory antibiotic concentrations has implications for understanding the emergence of multidrug resistance in bacteria. article_processing_charge: No article_type: original author: - first_name: Tobias full_name: Bergmiller, Tobias id: 2C471CFA-F248-11E8-B48F-1D18A9856A87 last_name: Bergmiller orcid: 0000-0001-5396-4346 - first_name: Anna M full_name: Andersson, Anna M id: 2B8A40DA-F248-11E8-B48F-1D18A9856A87 last_name: Andersson orcid: 0000-0003-2912-6769 - first_name: Kathrin full_name: Tomasek, Kathrin id: 3AEC8556-F248-11E8-B48F-1D18A9856A87 last_name: Tomasek orcid: 0000-0003-3768-877X - first_name: Enrique full_name: Balleza, Enrique last_name: Balleza - first_name: Daniel full_name: Kiviet, Daniel last_name: Kiviet - first_name: Robert full_name: Hauschild, Robert id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87 last_name: Hauschild orcid: 0000-0001-9843-3522 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. 2017;356(6335):311-315. doi:10.1126/science.aaf4762 apa: Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aaf4762 chicago: Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aaf4762. ieee: T. Bergmiller et al., “Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity,” Science, vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315, 2017. ista: Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik G, Guet CC. 2017. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. 356(6335), 311–315. mla: Bergmiller, Tobias, et al. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” Science, vol. 356, no. 6335, American Association for the Advancement of Science, 2017, pp. 311–15, doi:10.1126/science.aaf4762. short: T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, Science 356 (2017) 311–315. date_created: 2018-12-11T11:47:48Z date_published: 2017-04-21T00:00:00Z date_updated: 2024-02-21T13:49:00Z day: '21' department: - _id: CaGu - _id: GaTk - _id: Bio doi: 10.1126/science.aaf4762 intvolume: ' 356' issue: '6335' language: - iso: eng month: '04' oa_version: None page: 311 - 315 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Science publication_identifier: issn: - '00368075' publication_status: published publisher: American Association for the Advancement of Science publist_id: '7064' quality_controlled: '1' related_material: record: - id: '5560' relation: popular_science status: public scopus_import: 1 status: public title: Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 356 year: '2017' ... --- _id: '735' abstract: - lang: eng text: Cell-cell contact formation constitutes an essential step in evolution, leading to the differentiation of specialized cell types. However, remarkably little is known about whether and how the interplay between contact formation and fate specification affects development. Here, we identify a positive feedback loop between cell-cell contact duration, morphogen signaling, and mesendoderm cell-fate specification during zebrafish gastrulation. We show that long-lasting cell-cell contacts enhance the competence of prechordal plate (ppl) progenitor cells to respond to Nodal signaling, required for ppl cell-fate specification. We further show that Nodal signaling promotes ppl cell-cell contact duration, generating a positive feedback loop between ppl cell-cell contact duration and cell-fate specification. Finally, by combining mathematical modeling and experimentation, we show that this feedback determines whether anterior axial mesendoderm cells become ppl or, instead, turn into endoderm. Thus, the interdependent activities of cell-cell signaling and contact formation control fate diversification within the developing embryo. article_processing_charge: No author: - first_name: Vanessa full_name: Barone, Vanessa id: 419EECCC-F248-11E8-B48F-1D18A9856A87 last_name: Barone orcid: 0000-0003-2676-3367 - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Gabriel full_name: Krens, Gabriel id: 2B819732-F248-11E8-B48F-1D18A9856A87 last_name: Krens orcid: 0000-0003-4761-5996 - first_name: Saurabh full_name: Pradhan, Saurabh last_name: Pradhan - first_name: Shayan full_name: Shamipour, Shayan id: 40B34FE2-F248-11E8-B48F-1D18A9856A87 last_name: Shamipour - first_name: Keisuke full_name: Sako, Keisuke id: 3BED66BE-F248-11E8-B48F-1D18A9856A87 last_name: Sako orcid: 0000-0002-6453-8075 - first_name: Mateusz K full_name: Sikora, Mateusz K id: 2F74BCDE-F248-11E8-B48F-1D18A9856A87 last_name: Sikora - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Carl-Philipp J full_name: Heisenberg, Carl-Philipp J id: 39427864-F248-11E8-B48F-1D18A9856A87 last_name: Heisenberg orcid: 0000-0002-0912-4566 citation: ama: Barone V, Lang M, Krens G, et al. An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. Developmental Cell. 2017;43(2):198-211. doi:10.1016/j.devcel.2017.09.014 apa: Barone, V., Lang, M., Krens, G., Pradhan, S., Shamipour, S., Sako, K., … Heisenberg, C.-P. J. (2017). An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. Developmental Cell. Cell Press. https://doi.org/10.1016/j.devcel.2017.09.014 chicago: Barone, Vanessa, Moritz Lang, Gabriel Krens, Saurabh Pradhan, Shayan Shamipour, Keisuke Sako, Mateusz K Sikora, Calin C Guet, and Carl-Philipp J Heisenberg. “An Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling Determines Cell Fate.” Developmental Cell. Cell Press, 2017. https://doi.org/10.1016/j.devcel.2017.09.014. ieee: V. Barone et al., “An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate,” Developmental Cell, vol. 43, no. 2. Cell Press, pp. 198–211, 2017. ista: Barone V, Lang M, Krens G, Pradhan S, Shamipour S, Sako K, Sikora MK, Guet CC, Heisenberg C-PJ. 2017. An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. Developmental Cell. 43(2), 198–211. mla: Barone, Vanessa, et al. “An Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling Determines Cell Fate.” Developmental Cell, vol. 43, no. 2, Cell Press, 2017, pp. 198–211, doi:10.1016/j.devcel.2017.09.014. short: V. Barone, M. Lang, G. Krens, S. Pradhan, S. Shamipour, K. Sako, M.K. Sikora, C.C. Guet, C.-P.J. Heisenberg, Developmental Cell 43 (2017) 198–211. date_created: 2018-12-11T11:48:13Z date_published: 2017-10-23T00:00:00Z date_updated: 2024-03-27T23:30:38Z day: '23' department: - _id: CaHe - _id: CaGu - _id: GaTk doi: 10.1016/j.devcel.2017.09.014 ec_funded: 1 external_id: isi: - '000413443700011' intvolume: ' 43' isi: 1 issue: '2' language: - iso: eng month: '10' oa_version: None page: 198 - 211 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 252DD2A6-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: I2058 name: 'Cell segregation in gastrulation: the role of cell fate specification' publication: Developmental Cell publication_identifier: issn: - '15345807' publication_status: published publisher: Cell Press publist_id: '6934' quality_controlled: '1' related_material: record: - id: '961' relation: dissertation_contains status: public - id: '8350' relation: dissertation_contains status: public scopus_import: '1' status: public title: An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 43 year: '2017' ... --- _id: '1082' abstract: - lang: eng text: In many applications, it is desirable to extract only the relevant aspects of data. A principled way to do this is the information bottleneck (IB) method, where one seeks a code that maximises information about a relevance variable, Y, while constraining the information encoded about the original data, X. Unfortunately however, the IB method is computationally demanding when data are high-dimensional and/or non-gaussian. Here we propose an approximate variational scheme for maximising a lower bound on the IB objective, analogous to variational EM. Using this method, we derive an IB algorithm to recover features that are both relevant and sparse. Finally, we demonstrate how kernelised versions of the algorithm can be used to address a broad range of problems with non-linear relation between X and Y. alternative_title: - Advances in Neural Information Processing Systems author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: 'Chalk MJ, Marre O, Tkačik G. Relevant sparse codes with variational information bottleneck. In: Vol 29. Neural Information Processing Systems; 2016:1965-1973.' apa: 'Chalk, M. J., Marre, O., & Tkačik, G. (2016). Relevant sparse codes with variational information bottleneck (Vol. 29, pp. 1965–1973). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information Processing Systems.' chicago: Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Relevant Sparse Codes with Variational Information Bottleneck,” 29:1965–73. Neural Information Processing Systems, 2016. ieee: 'M. J. Chalk, O. Marre, and G. Tkačik, “Relevant sparse codes with variational information bottleneck,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain, 2016, vol. 29, pp. 1965–1973.' ista: 'Chalk MJ, Marre O, Tkačik G. 2016. Relevant sparse codes with variational information bottleneck. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 1965–1973.' mla: Chalk, Matthew J., et al. Relevant Sparse Codes with Variational Information Bottleneck. Vol. 29, Neural Information Processing Systems, 2016, pp. 1965–73. short: M.J. Chalk, O. Marre, G. Tkačik, in:, Neural Information Processing Systems, 2016, pp. 1965–1973. conference: end_date: 2016-12-10 location: Barcelona, Spain name: 'NIPS: Neural Information Processing Systems' start_date: 2016-12-05 date_created: 2018-12-11T11:50:03Z date_published: 2016-12-01T00:00:00Z date_updated: 2021-01-12T06:48:09Z day: '01' department: - _id: GaTk intvolume: ' 29' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1605.07332 month: '12' oa: 1 oa_version: Preprint page: 1965-1973 publication_status: published publisher: Neural Information Processing Systems publist_id: '6298' quality_controlled: '1' related_material: link: - relation: other url: https://papers.nips.cc/paper/6101-relevant-sparse-codes-with-variational-information-bottleneck scopus_import: 1 status: public title: Relevant sparse codes with variational information bottleneck type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 29 year: '2016' ... --- _id: '1105' abstract: - lang: eng text: Jointly characterizing neural responses in terms of several external variables promises novel insights into circuit function, but remains computationally prohibitive in practice. Here we use gaussian process (GP) priors and exploit recent advances in fast GP inference and learning based on Kronecker methods, to efficiently estimate multidimensional nonlinear tuning functions. Our estimator require considerably less data than traditional methods and further provides principled uncertainty estimates. We apply these tools to hippocampal recordings during open field exploration and use them to characterize the joint dependence of CA1 responses on the position of the animal and several other variables, including the animal\'s speed, direction of motion, and network oscillations.Our results provide an unprecedentedly detailed quantification of the tuning of hippocampal neurons. The model\'s generality suggests that our approach can be used to estimate neural response properties in other brain regions. acknowledgement: "We thank Jozsef Csicsvari for kindly sharing the CA1 data.\r\nThis work was supported by the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme(FP7/2007-2013) under REA grant agreement no. 291734." alternative_title: - Advances in Neural Information Processing Systems author: - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: 'Savin C, Tkačik G. Estimating nonlinear neural response functions using GP priors and Kronecker methods. In: Vol 29. Neural Information Processing Systems; 2016:3610-3618.' apa: 'Savin, C., & Tkačik, G. (2016). Estimating nonlinear neural response functions using GP priors and Kronecker methods (Vol. 29, pp. 3610–3618). Presented at the NIPS: Neural Information Processing Systems, Barcelona; Spain: Neural Information Processing Systems.' chicago: Savin, Cristina, and Gašper Tkačik. “Estimating Nonlinear Neural Response Functions Using GP Priors and Kronecker Methods,” 29:3610–18. Neural Information Processing Systems, 2016. ieee: 'C. Savin and G. Tkačik, “Estimating nonlinear neural response functions using GP priors and Kronecker methods,” presented at the NIPS: Neural Information Processing Systems, Barcelona; Spain, 2016, vol. 29, pp. 3610–3618.' ista: 'Savin C, Tkačik G. 2016. Estimating nonlinear neural response functions using GP priors and Kronecker methods. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 3610–3618.' mla: Savin, Cristina, and Gašper Tkačik. Estimating Nonlinear Neural Response Functions Using GP Priors and Kronecker Methods. Vol. 29, Neural Information Processing Systems, 2016, pp. 3610–18. short: C. Savin, G. Tkačik, in:, Neural Information Processing Systems, 2016, pp. 3610–3618. conference: end_date: 2016-12-10 location: Barcelona; Spain name: 'NIPS: Neural Information Processing Systems' start_date: 2016-12-05 date_created: 2018-12-11T11:50:10Z date_published: 2016-12-01T00:00:00Z date_updated: 2021-01-12T06:48:19Z day: '01' department: - _id: GaTk ec_funded: 1 intvolume: ' 29' language: - iso: eng main_file_link: - url: http://papers.nips.cc/paper/6153-estimating-nonlinear-neural-response-functions-using-gp-priors-and-kronecker-methods month: '12' oa_version: None page: 3610-3618 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication_status: published publisher: Neural Information Processing Systems publist_id: '6265' quality_controlled: '1' scopus_import: 1 status: public title: Estimating nonlinear neural response functions using GP priors and Kronecker methods type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 29 year: '2016' ... --- _id: '1170' abstract: - lang: eng text: The increasing complexity of dynamic models in systems and synthetic biology poses computational challenges especially for the identification of model parameters. While modularization of the corresponding optimization problems could help reduce the “curse of dimensionality,” abundant feedback and crosstalk mechanisms prohibit a simple decomposition of most biomolecular networks into subnetworks, or modules. Drawing on ideas from network modularization and multiple-shooting optimization, we present here a modular parameter identification approach that explicitly allows for such interdependencies. Interfaces between our modules are given by the experimentally measured molecular species. This definition allows deriving good (initial) estimates for the inter-module communication directly from the experimental data. Given these estimates, the states and parameter sensitivities of different modules can be integrated independently. To achieve consistency between modules, we iteratively adjust the estimates for inter-module communication while optimizing the parameters. After convergence to an optimal parameter set---but not during earlier iterations---the intermodule communication as well as the individual modules\' state dynamics agree with the dynamics of the nonmodularized network. Our modular parameter identification approach allows for easy parallelization; it can reduce the computational complexity for larger networks and decrease the probability to converge to suboptimal local minima. We demonstrate the algorithm\'s performance in parameter estimation for two biomolecular networks, a synthetic genetic oscillator and a mammalian signaling pathway. author: - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Jörg full_name: Stelling, Jörg last_name: Stelling citation: ama: Lang M, Stelling J. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 2016;38(6):B988-B1008. doi:10.1137/15M103306X apa: Lang, M., & Stelling, J. (2016). Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. Society for Industrial and Applied Mathematics . https://doi.org/10.1137/15M103306X chicago: Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular Networks.” SIAM Journal on Scientific Computing. Society for Industrial and Applied Mathematics , 2016. https://doi.org/10.1137/15M103306X. ieee: M. Lang and J. Stelling, “Modular parameter identification of biomolecular networks,” SIAM Journal on Scientific Computing, vol. 38, no. 6. Society for Industrial and Applied Mathematics , pp. B988–B1008, 2016. ista: Lang M, Stelling J. 2016. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 38(6), B988–B1008. mla: Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular Networks.” SIAM Journal on Scientific Computing, vol. 38, no. 6, Society for Industrial and Applied Mathematics , 2016, pp. B988–1008, doi:10.1137/15M103306X. short: M. Lang, J. Stelling, SIAM Journal on Scientific Computing 38 (2016) B988–B1008. date_created: 2018-12-11T11:50:31Z date_published: 2016-11-15T00:00:00Z date_updated: 2021-01-12T06:48:49Z day: '15' ddc: - '003' - '518' - '570' - '621' department: - _id: CaGu - _id: GaTk doi: 10.1137/15M103306X file: - access_level: local checksum: 781bc3ffd30b2dd65b7727c5a285fc78 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:41Z date_updated: 2020-07-14T12:44:37Z file_id: '5095' file_name: IST-2017-811-v1+1_modular_parameter_identification.pdf file_size: 871964 relation: main_file file_date_updated: 2020-07-14T12:44:37Z has_accepted_license: '1' intvolume: ' 38' issue: '6' language: - iso: eng month: '11' oa_version: Submitted Version page: B988 - B1008 publication: SIAM Journal on Scientific Computing publication_status: published publisher: 'Society for Industrial and Applied Mathematics ' publist_id: '6186' pubrep_id: '811' quality_controlled: '1' scopus_import: 1 status: public title: Modular parameter identification of biomolecular networks type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2016' ... --- _id: '1171' author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: 'Tkačik G. Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on &quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&quot; by O. C. Martin et al. Physics of Life Reviews. 2016;17:166-167. doi:10.1016/j.plrev.2016.06.005' apa: 'Tkačik, G. (2016). Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on &quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&quot; by O. C. Martin et al. Physics of Life Reviews. Elsevier. https://doi.org/10.1016/j.plrev.2016.06.005' chicago: 'Tkačik, Gašper. “Understanding Regulatory Networks Requires More than Computing a Multitude of Graph Statistics: Comment on &quot;Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function&quot; by O. C. Martin et Al.” Physics of Life Reviews. Elsevier, 2016. https://doi.org/10.1016/j.plrev.2016.06.005.' ieee: 'G. Tkačik, “Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on &quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&quot; by O. C. Martin et al.,” Physics of Life Reviews, vol. 17. Elsevier, pp. 166–167, 2016.' ista: 'Tkačik G. 2016. Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on &quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&quot; by O. C. Martin et al. Physics of Life Reviews. 17, 166–167.' mla: 'Tkačik, Gašper. “Understanding Regulatory Networks Requires More than Computing a Multitude of Graph Statistics: Comment on &quot;Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function&quot; by O. C. Martin et Al.” Physics of Life Reviews, vol. 17, Elsevier, 2016, pp. 166–67, doi:10.1016/j.plrev.2016.06.005.' short: G. Tkačik, Physics of Life Reviews 17 (2016) 166–167. date_created: 2018-12-11T11:50:32Z date_published: 2016-07-01T00:00:00Z date_updated: 2021-01-12T06:48:50Z day: '01' department: - _id: GaTk doi: 10.1016/j.plrev.2016.06.005 intvolume: ' 17' language: - iso: eng month: '07' oa_version: None page: 166 - 167 publication: Physics of Life Reviews publication_status: published publisher: Elsevier publist_id: '6185' quality_controlled: '1' scopus_import: 1 status: public title: 'Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O. C. Martin et al.' type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 17 year: '2016' ... --- _id: '1188' abstract: - lang: eng text: "We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. \r\nIn the asymptotic regime of slow\r\ndiffusion, that coincides with the relevant experimental range, the resulting\r\nnon-linear Fokker–Planck equation is solved for the steady state in the WKB\r\napproximation that maps it into the ground state of a quantum particle in an\r\nAiry potential plus a centrifugal term. We retrieve scaling laws for growth rate\r\nfluctuations and time response with respect to the distance from the maximum\r\ngrowth rate suggesting that suboptimal populations can have a faster response\r\nto perturbations." acknowledgement: D De Martino is supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. D Masoero is supported by the FCT scholarship, number SFRH/BPD/75908/2011. D De Martino thanks the Grupo de Física Matemática of the Universidade de Lisboa for the kind hospitality. We also wish to thank Matteo Osella, Vincenzo Vitagliano and Vera Luz Masoero for useful discussions, also late at night. article_number: '123502' author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Davide full_name: Masoero, Davide last_name: Masoero citation: ama: 'De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth. Journal of Statistical Mechanics: Theory and Experiment. 2016;2016(12). doi:10.1088/1742-5468/aa4e8f' apa: 'De Martino, D., & Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa4e8f' chicago: 'De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism &amp; Growth.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2016. https://doi.org/10.1088/1742-5468/aa4e8f.' ieee: 'D. De Martino and D. Masoero, “Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 12. IOPscience, 2016.' ista: 'De Martino D, Masoero D. 2016. Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth. Journal of Statistical Mechanics: Theory and Experiment. 2016(12), 123502.' mla: 'De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism &amp; Growth.” Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 12, 123502, IOPscience, 2016, doi:10.1088/1742-5468/aa4e8f.' short: 'D. De Martino, D. Masoero, Journal of Statistical Mechanics: Theory and Experiment 2016 (2016).' date_created: 2018-12-11T11:50:37Z date_published: 2016-12-30T00:00:00Z date_updated: 2021-01-12T06:48:57Z day: '30' department: - _id: GaTk doi: 10.1088/1742-5468/aa4e8f ec_funded: 1 intvolume: ' 2016' issue: '12' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1606.09048 month: '12' oa: 1 oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Journal of Statistical Mechanics: Theory and Experiment' publication_status: published publisher: IOPscience publist_id: '6165' quality_controlled: '1' scopus_import: 1 status: public title: Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 2016 year: '2016' ... --- _id: '1203' abstract: - lang: eng text: Haemophilus haemolyticus has been recently discovered to have the potential to cause invasive disease. It is closely related to nontypeable Haemophilus influenzae (NT H. influenzae). NT H. influenzae and H. haemolyticus are often misidentified because none of the existing tests targeting the known phenotypes of H. haemolyticus are able to specifically identify H. haemolyticus. Through comparative genomic analysis of H. haemolyticus and NT H. influenzae, we identified genes unique to H. haemolyticus that can be used as targets for the identification of H. haemolyticus. A real-time PCR targeting purT (encoding phosphoribosylglycinamide formyltransferase 2 in the purine synthesis pathway) was developed and evaluated. The lower limit of detection was 40 genomes/PCR; the sensitivity and specificity in detecting H. haemolyticus were 98.9% and 97%, respectively. To improve the discrimination of H. haemolyticus and NT H. influenzae, a testing scheme combining two targets (H. haemolyticus purT and H. influenzae hpd, encoding protein D lipoprotein) was also evaluated and showed 96.7% sensitivity and 98.2% specificity for the identification of H. haemolyticus and 92.8% sensitivity and 100% specificity for the identification of H. influenzae, respectively. The dual-target testing scheme can be used for the diagnosis and surveillance of infection and disease caused by H. haemolyticus and NT H. influenzae. acknowledgement: We are grateful to ABCs for providing strains and the Bacterial Meningitis Laboratory for technical support. author: - first_name: Fang full_name: Hu, Fang last_name: Hu - first_name: Lavanya full_name: Rishishwar, Lavanya last_name: Rishishwar - first_name: Ambily full_name: Sivadas, Ambily last_name: Sivadas - first_name: Gabriel full_name: Mitchell, Gabriel id: 315BCD80-F248-11E8-B48F-1D18A9856A87 last_name: Mitchell - first_name: Jordan full_name: King, Jordan last_name: King - first_name: Timothy full_name: Murphy, Timothy last_name: Murphy - first_name: Janet full_name: Gilsdorf, Janet last_name: Gilsdorf - first_name: Leonard full_name: Mayer, Leonard last_name: Mayer - first_name: Xin full_name: Wang, Xin last_name: Wang citation: ama: Hu F, Rishishwar L, Sivadas A, et al. Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. 2016;54(12):3010-3017. doi:10.1128/JCM.01511-16 apa: Hu, F., Rishishwar, L., Sivadas, A., Mitchell, G., King, J., Murphy, T., … Wang, X. (2016). Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. American Society for Microbiology. https://doi.org/10.1128/JCM.01511-16 chicago: Hu, Fang, Lavanya Rishishwar, Ambily Sivadas, Gabriel Mitchell, Jordan King, Timothy Murphy, Janet Gilsdorf, Leonard Mayer, and Xin Wang. “Comparative Genomic Analysis of Haemophilus Haemolyticus and Nontypeable Haemophilus Influenzae and a New Testing Scheme for Their Discrimination.” Journal of Clinical Microbiology. American Society for Microbiology, 2016. https://doi.org/10.1128/JCM.01511-16. ieee: F. Hu et al., “Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination,” Journal of Clinical Microbiology, vol. 54, no. 12. American Society for Microbiology, pp. 3010–3017, 2016. ista: Hu F, Rishishwar L, Sivadas A, Mitchell G, King J, Murphy T, Gilsdorf J, Mayer L, Wang X. 2016. Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. 54(12), 3010–3017. mla: Hu, Fang, et al. “Comparative Genomic Analysis of Haemophilus Haemolyticus and Nontypeable Haemophilus Influenzae and a New Testing Scheme for Their Discrimination.” Journal of Clinical Microbiology, vol. 54, no. 12, American Society for Microbiology, 2016, pp. 3010–17, doi:10.1128/JCM.01511-16. short: F. Hu, L. Rishishwar, A. Sivadas, G. Mitchell, J. King, T. Murphy, J. Gilsdorf, L. Mayer, X. Wang, Journal of Clinical Microbiology 54 (2016) 3010–3017. date_created: 2018-12-11T11:50:41Z date_published: 2016-12-01T00:00:00Z date_updated: 2021-01-12T06:49:04Z day: '01' department: - _id: GaTk doi: 10.1128/JCM.01511-16 intvolume: ' 54' issue: '12' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5121393/ month: '12' oa: 1 oa_version: Submitted Version page: 3010 - 3017 publication: Journal of Clinical Microbiology publication_status: published publisher: American Society for Microbiology publist_id: '6146' quality_controlled: '1' scopus_import: 1 status: public title: Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 54 year: '2016' ... --- _id: '1214' abstract: - lang: eng text: 'With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. While very successful with classical robots, these methods run into severe difficulties when applied to soft robots, a new field of robotics with large interest for human-robot interaction. We claim that a novel controller paradigm opens new perspective for this field. This paper applies a recently developed neuro controller with differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object''s internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently develops to rotate it. In this way, the robot discovers affordances of objects its body is interacting with.' acknowledgement: RD thanks for the hospitality at the Max-Planck-Institute and for helpful discussions with Nihat Ay and Keyan Zahedi. article_number: '7759138' author: - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius - first_name: Raphael full_name: Hostettler, Raphael last_name: Hostettler - first_name: Alois full_name: Knoll, Alois last_name: Knoll - first_name: Ralf full_name: Der, Ralf last_name: Der citation: ama: 'Martius GS, Hostettler R, Knoll A, Der R. Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm. In: Vol 2016-November. IEEE; 2016. doi:10.1109/IROS.2016.7759138' apa: 'Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm (Vol. 2016–November). Presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea: IEEE. https://doi.org/10.1109/IROS.2016.7759138' chicago: 'Martius, Georg S, Raphael Hostettler, Alois Knoll, and Ralf Der. “Compliant Control for Soft Robots: Emergent Behavior of a Tendon Driven Anthropomorphic Arm,” Vol. 2016–November. IEEE, 2016. https://doi.org/10.1109/IROS.2016.7759138.' ieee: 'G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm,” presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea, 2016, vol. 2016–November.' ista: 'Martius GS, Hostettler R, Knoll A, Der R. 2016. Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm. IEEE RSJ International Conference on Intelligent Robots and Systems IROS vol. 2016–November, 7759138.' mla: 'Martius, Georg S., et al. Compliant Control for Soft Robots: Emergent Behavior of a Tendon Driven Anthropomorphic Arm. Vol. 2016–November, 7759138, IEEE, 2016, doi:10.1109/IROS.2016.7759138.' short: G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, IEEE, 2016. conference: end_date: 2016-09-14 location: Daejeon, Korea name: 'IEEE RSJ International Conference on Intelligent Robots and Systems IROS ' start_date: 2016-09-09 date_created: 2018-12-11T11:50:45Z date_published: 2016-11-28T00:00:00Z date_updated: 2021-01-12T06:49:08Z day: '28' department: - _id: ChLa - _id: GaTk doi: 10.1109/IROS.2016.7759138 language: - iso: eng month: '11' oa_version: None publication_status: published publisher: IEEE publist_id: '6121' quality_controlled: '1' scopus_import: 1 status: public title: 'Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm' type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 2016-November year: '2016' ... --- _id: '1220' abstract: - lang: eng text: Theoretical and numerical aspects of aerodynamic efficiency of propulsion systems coupled to the boundary layer of a fuselage are studied. We discuss the effects of local flow fields, which are affected both by conservative flow acceleration as well as total pressure losses, on the efficiency of boundary layer immersed propulsion devices. We introduce the concept of a boundary layer retardation turbine that helps reduce skin friction over the fuselage. We numerically investigate efficiency gains offered by boundary layer and wake interacting devices. We discuss the results in terms of a total energy consumption framework and show that efficiency gains of any device depend on all the other elements of the propulsion system. author: - first_name: Gregor full_name: Mikić, Gregor last_name: Mikić - first_name: Alex full_name: Stoll, Alex last_name: Stoll - first_name: Joe full_name: Bevirt, Joe last_name: Bevirt - first_name: Rok full_name: Grah, Rok id: 483E70DE-F248-11E8-B48F-1D18A9856A87 last_name: Grah orcid: 0000-0003-2539-3560 - first_name: Mark full_name: Moore, Mark last_name: Moore citation: ama: 'Mikić G, Stoll A, Bevirt J, Grah R, Moore M. Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency. In: AIAA; 2016:1-19. doi:10.2514/6.2016-3764' apa: 'Mikić, G., Stoll, A., Bevirt, J., Grah, R., & Moore, M. (2016). Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency (pp. 1–19). Presented at the AIAA: Aviation Technology, Integration, and Operations Conference, Washington, D.C., USA: AIAA. https://doi.org/10.2514/6.2016-3764' chicago: Mikić, Gregor, Alex Stoll, Joe Bevirt, Rok Grah, and Mark Moore. “Fuselage Boundary Layer Ingestion Propulsion Applied to a Thin Haul Commuter Aircraft for Optimal Efficiency,” 1–19. AIAA, 2016. https://doi.org/10.2514/6.2016-3764. ieee: 'G. Mikić, A. Stoll, J. Bevirt, R. Grah, and M. Moore, “Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency,” presented at the AIAA: Aviation Technology, Integration, and Operations Conference, Washington, D.C., USA, 2016, pp. 1–19.' ista: 'Mikić G, Stoll A, Bevirt J, Grah R, Moore M. 2016. Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency. AIAA: Aviation Technology, Integration, and Operations Conference, 1–19.' mla: Mikić, Gregor, et al. Fuselage Boundary Layer Ingestion Propulsion Applied to a Thin Haul Commuter Aircraft for Optimal Efficiency. AIAA, 2016, pp. 1–19, doi:10.2514/6.2016-3764. short: G. Mikić, A. Stoll, J. Bevirt, R. Grah, M. Moore, in:, AIAA, 2016, pp. 1–19. conference: end_date: 2016-06-17 location: Washington, D.C., USA name: 'AIAA: Aviation Technology, Integration, and Operations Conference' start_date: 2016-06-13 date_created: 2018-12-11T11:50:47Z date_published: 2016-06-01T00:00:00Z date_updated: 2023-02-21T10:17:50Z day: '01' department: - _id: CaGu - _id: GaTk doi: 10.2514/6.2016-3764 language: - iso: eng main_file_link: - open_access: '1' url: https://ntrs.nasa.gov/search.jsp?R=20160010167&hterms=Fuselage+boundary+layer+ingestion+propulsion+applied+thin+haul+commuter+aircraft+optimal+efficiency&qs=N%3D0%26Ntk%3DAll%26Ntt%3DFuselage%2520boundary%2520layer%2520ingestion%2520propulsion%2520applied%2520to%2520a%2520thin%2520haul%2520commuter%2520aircraft%2520for%2520optimal%2520efficiency%26Ntx%3Dmode%2520matchallpartial%26Nm%3D123%7CCollection%7CNASA%2520STI%7C%7C17%7CCollection%7CNACA month: '06' oa: 1 oa_version: Preprint page: 1 - 19 publication_status: published publisher: AIAA publist_id: '6114' quality_controlled: '1' scopus_import: 1 status: public title: Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 year: '2016' ... --- _id: '1242' abstract: - lang: eng text: A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression. acknowledgement: "We thank T. Gregor, A. Prochaintz, and others for\r\nhelpful discussions. This work was supported in part by\r\nGrants No. PHY-1305525 and No. CCF-0939370 from the\r\nUS National Science Foundation and by the W.M. Keck\r\nFoundation. A.M.W. acknowledges the support by European\r\nResearch Council (ERC) Grant No. MCCIG PCIG10–GA-\r\n2011–303561. G.T. and T.R.S. were supported by Austrian\r\nScience Fund (FWF) Grant No. P28844S." article_number: '022404' author: - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Aleksandra full_name: Walczak, Aleksandra last_name: Walczak - first_name: William full_name: Bialek, William last_name: Bialek - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Sokolowski TR, Walczak A, Bialek W, Tkačik G. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2016;93(2). doi:10.1103/PhysRevE.93.022404 apa: Sokolowski, T. R., Walczak, A., Bialek, W., & Tkačik, G. (2016). Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.93.022404 chicago: Sokolowski, Thomas R, Aleksandra Walczak, William Bialek, and Gašper Tkačik. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics, 2016. https://doi.org/10.1103/PhysRevE.93.022404. ieee: T. R. Sokolowski, A. Walczak, W. Bialek, and G. Tkačik, “Extending the dynamic range of transcription factor action by translational regulation,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 93, no. 2. American Institute of Physics, 2016. ista: Sokolowski TR, Walczak A, Bialek W, Tkačik G. 2016. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. 93(2), 022404. mla: Sokolowski, Thomas R., et al. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 93, no. 2, 022404, American Institute of Physics, 2016, doi:10.1103/PhysRevE.93.022404. short: T.R. Sokolowski, A. Walczak, W. Bialek, G. Tkačik, Physical Review E Statistical Nonlinear and Soft Matter Physics 93 (2016). date_created: 2018-12-11T11:50:54Z date_published: 2016-02-04T00:00:00Z date_updated: 2021-01-12T06:49:20Z day: '04' department: - _id: GaTk doi: 10.1103/PhysRevE.93.022404 intvolume: ' 93' issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1507.02562 month: '02' oa: 1 oa_version: Preprint project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Physical Review E Statistical Nonlinear and Soft Matter Physics publication_status: published publisher: American Institute of Physics publist_id: '6088' quality_controlled: '1' scopus_import: 1 status: public title: Extending the dynamic range of transcription factor action by translational regulation type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 93 year: '2016' ... --- _id: '1244' abstract: - lang: eng text: Cell polarity refers to a functional spatial organization of proteins that is crucial for the control of essential cellular processes such as growth and division. To establish polarity, cells rely on elaborate regulation networks that control the distribution of proteins at the cell membrane. In fission yeast cells, a microtubule-dependent network has been identified that polarizes the distribution of signaling proteins that restricts growth to cell ends and targets the cytokinetic machinery to the middle of the cell. Although many molecular components have been shown to play a role in this network, it remains unknown which molecular functionalities are minimally required to establish a polarized protein distribution in this system. Here we show that a membrane-binding protein fragment, which distributes homogeneously in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching it to a cytoplasmic microtubule end-binding protein. This concentration results in a polarized pattern of chimera proteins with a spatial extension that is very reminiscent of natural polarity patterns in fission yeast. However, chimera levels fluctuate in response to microtubule dynamics, and disruption of microtubules leads to disappearance of the pattern. Numerical simulations confirm that the combined functionality of membrane anchoring and microtubule tip affinity is in principle sufficient to create polarized patterns. Our chimera protein may thus represent a simple molecular functionality that is able to polarize the membrane, onto which additional layers of molecular complexity may be built to provide the temporal robustness that is typical of natural polarity patterns. acknowledgement: "We thank Sophie Martin, Ken Sawin, Stephen Huisman,\r\nand Damian Brunner for strains; Julianne\r\nTeapal, Marcel Janson, Sergio Rincon,\r\nand Phong Tran for technical assistance; Andrew Mugler and Bela Mulder for\r\ndiscussions; and Sander Tans, Phong Tran,\r\nand Anne Paoletti for critical reading\r\nof the manuscript. This work is part of the research program of the\r\n“\r\nStichting\r\nvoor Fundamenteel Onderzoek de Materie,\r\n”\r\nwhich is financially supported by\r\nthe\r\n“\r\nNederlandse organisatie voor Wete\r\nnschappelijk Onderzoek (NWO).\r\n”" author: - first_name: Pierre full_name: Recouvreux, Pierre last_name: Recouvreux - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Aristea full_name: Grammoustianou, Aristea last_name: Grammoustianou - first_name: Pieter full_name: Tenwolde, Pieter last_name: Tenwolde - first_name: Marileen full_name: Dogterom, Marileen last_name: Dogterom citation: ama: Recouvreux P, Sokolowski TR, Grammoustianou A, Tenwolde P, Dogterom M. Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. 2016;113(7):1811-1816. doi:10.1073/pnas.1419248113 apa: Recouvreux, P., Sokolowski, T. R., Grammoustianou, A., Tenwolde, P., & Dogterom, M. (2016). Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1419248113 chicago: Recouvreux, Pierre, Thomas R Sokolowski, Aristea Grammoustianou, Pieter Tenwolde, and Marileen Dogterom. “Chimera Proteins with Affinity for Membranes and Microtubule Tips Polarize in the Membrane of Fission Yeast Cells.” PNAS. National Academy of Sciences, 2016. https://doi.org/10.1073/pnas.1419248113. ieee: P. Recouvreux, T. R. Sokolowski, A. Grammoustianou, P. Tenwolde, and M. Dogterom, “Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells,” PNAS, vol. 113, no. 7. National Academy of Sciences, pp. 1811–1816, 2016. ista: Recouvreux P, Sokolowski TR, Grammoustianou A, Tenwolde P, Dogterom M. 2016. Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. 113(7), 1811–1816. mla: Recouvreux, Pierre, et al. “Chimera Proteins with Affinity for Membranes and Microtubule Tips Polarize in the Membrane of Fission Yeast Cells.” PNAS, vol. 113, no. 7, National Academy of Sciences, 2016, pp. 1811–16, doi:10.1073/pnas.1419248113. short: P. Recouvreux, T.R. Sokolowski, A. Grammoustianou, P. Tenwolde, M. Dogterom, PNAS 113 (2016) 1811–1816. date_created: 2018-12-11T11:50:55Z date_published: 2016-02-16T00:00:00Z date_updated: 2021-01-12T06:49:21Z day: '16' department: - _id: GaTk doi: 10.1073/pnas.1419248113 intvolume: ' 113' issue: '7' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763754/ month: '02' oa: 1 oa_version: Submitted Version page: 1811 - 1816 publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '6085' quality_controlled: '1' scopus_import: 1 status: public title: Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 113 year: '2016' ... --- _id: '1248' abstract: - lang: eng text: Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been possible to measure, directly, the flow of information in biological networks, or more generally where information-theoretic ideas have been used to guide the analysis of experiments. Systems of interest range from single molecules (the sequence diversity in families of proteins) to groups of organisms (the distribution of velocities in flocks of birds), and all scales in between. Many of these analyses are motivated by the idea that biological systems may have evolved to optimize the gathering and representation of information, and we review the experimental evidence for this optimization, again across a wide range of scales. acknowledgement: "Our work was supported in part by the US\r\nNational Science Foundation (PHY–1305525 and CCF–\r\n0939370), by the Austrian Science Foundation (FWF\r\nP25651), by the Human Frontiers Science Program, and\r\nby the Simons and Swartz Foundations." author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Tkačik G, Bialek W. Information processing in living systems. Annual Review of Condensed Matter Physics. 2016;7:89-117. doi:10.1146/annurev-conmatphys-031214-014803 apa: Tkačik, G., & Bialek, W. (2016). Information processing in living systems. Annual Review of Condensed Matter Physics. Annual Reviews. https://doi.org/10.1146/annurev-conmatphys-031214-014803 chicago: Tkačik, Gašper, and William Bialek. “Information Processing in Living Systems.” Annual Review of Condensed Matter Physics. Annual Reviews, 2016. https://doi.org/10.1146/annurev-conmatphys-031214-014803. ieee: G. Tkačik and W. Bialek, “Information processing in living systems,” Annual Review of Condensed Matter Physics, vol. 7. Annual Reviews, pp. 89–117, 2016. ista: Tkačik G, Bialek W. 2016. Information processing in living systems. Annual Review of Condensed Matter Physics. 7, 89–117. mla: Tkačik, Gašper, and William Bialek. “Information Processing in Living Systems.” Annual Review of Condensed Matter Physics, vol. 7, Annual Reviews, 2016, pp. 89–117, doi:10.1146/annurev-conmatphys-031214-014803. short: G. Tkačik, W. Bialek, Annual Review of Condensed Matter Physics 7 (2016) 89–117. date_created: 2018-12-11T11:50:56Z date_published: 2016-03-10T00:00:00Z date_updated: 2021-01-12T06:49:23Z day: '10' department: - _id: GaTk doi: 10.1146/annurev-conmatphys-031214-014803 intvolume: ' 7' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1412.8752 month: '03' oa: 1 oa_version: Preprint page: 89 - 117 project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: Annual Review of Condensed Matter Physics publication_status: published publisher: Annual Reviews publist_id: '6080' quality_controlled: '1' scopus_import: 1 status: public title: Information processing in living systems type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 7 year: '2016' ... --- _id: '1260' abstract: - lang: eng text: In this work, the Gardner problem of inferring interactions and fields for an Ising neural network from given patterns under a local stability hypothesis is addressed under a dual perspective. By means of duality arguments, an integer linear system is defined whose solution space is the dual of the Gardner space and whose solutions represent mutually unstable patterns. We propose and discuss Monte Carlo methods in order to find and remove unstable patterns and uniformly sample the space of interactions thereafter. We illustrate the problem on a set of real data and perform ensemble calculation that shows how the emergence of phase dominated by unstable patterns can be triggered in a nonlinear discontinuous way. article_number: '1650067' article_processing_charge: No article_type: original author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: De Martino D. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 2016;27(6). doi:10.1142/S0129183116500674 apa: De Martino, D. (2016). The dual of the space of interactions in neural network models. International Journal of Modern Physics C. World Scientific Publishing. https://doi.org/10.1142/S0129183116500674 chicago: De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network Models.” International Journal of Modern Physics C. World Scientific Publishing, 2016. https://doi.org/10.1142/S0129183116500674. ieee: D. De Martino, “The dual of the space of interactions in neural network models,” International Journal of Modern Physics C, vol. 27, no. 6. World Scientific Publishing, 2016. ista: De Martino D. 2016. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 27(6), 1650067. mla: De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network Models.” International Journal of Modern Physics C, vol. 27, no. 6, 1650067, World Scientific Publishing, 2016, doi:10.1142/S0129183116500674. short: D. De Martino, International Journal of Modern Physics C 27 (2016). date_created: 2018-12-11T11:51:00Z date_published: 2016-06-01T00:00:00Z date_updated: 2021-01-12T06:49:28Z day: '01' department: - _id: GaTk doi: 10.1142/S0129183116500674 external_id: arxiv: - '1505.02963' intvolume: ' 27' issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1505.02963 month: '06' oa: 1 oa_version: Preprint publication: International Journal of Modern Physics C publication_status: published publisher: World Scientific Publishing publist_id: '6065' quality_controlled: '1' scopus_import: 1 status: public title: The dual of the space of interactions in neural network models type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 27 year: '2016' ... --- _id: '1266' abstract: - lang: eng text: 'Cortical networks exhibit ‘global oscillations’, in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a ‘prediction error’ while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code.' acknowledgement: Boris Gutkin acknowledges funding by the Russian Academic Excellence Project '5-100’. article_number: e13824 author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Boris full_name: Gutkin, Boris last_name: Gutkin - first_name: Sophie full_name: Denève, Sophie last_name: Denève citation: ama: Chalk MJ, Gutkin B, Denève S. Neural oscillations as a signature of efficient coding in the presence of synaptic delays. eLife. 2016;5(2016JULY). doi:10.7554/eLife.13824 apa: Chalk, M. J., Gutkin, B., & Denève, S. (2016). Neural oscillations as a signature of efficient coding in the presence of synaptic delays. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.13824 chicago: Chalk, Matthew J, Boris Gutkin, and Sophie Denève. “Neural Oscillations as a Signature of Efficient Coding in the Presence of Synaptic Delays.” ELife. eLife Sciences Publications, 2016. https://doi.org/10.7554/eLife.13824. ieee: M. J. Chalk, B. Gutkin, and S. Denève, “Neural oscillations as a signature of efficient coding in the presence of synaptic delays,” eLife, vol. 5, no. 2016JULY. eLife Sciences Publications, 2016. ista: Chalk MJ, Gutkin B, Denève S. 2016. Neural oscillations as a signature of efficient coding in the presence of synaptic delays. eLife. 5(2016JULY), e13824. mla: Chalk, Matthew J., et al. “Neural Oscillations as a Signature of Efficient Coding in the Presence of Synaptic Delays.” ELife, vol. 5, no. 2016JULY, e13824, eLife Sciences Publications, 2016, doi:10.7554/eLife.13824. short: M.J. Chalk, B. Gutkin, S. Denève, ELife 5 (2016). date_created: 2018-12-11T11:51:02Z date_published: 2016-07-01T00:00:00Z date_updated: 2021-01-12T06:49:30Z day: '01' ddc: - '571' department: - _id: GaTk doi: 10.7554/eLife.13824 file: - access_level: open_access checksum: dc52d967dc76174477bb258d84be2899 content_type: application/pdf creator: system date_created: 2018-12-12T10:11:20Z date_updated: 2020-07-14T12:44:42Z file_id: '4874' file_name: IST-2016-700-v1+1_e13824-download.pdf file_size: 2819055 relation: main_file file_date_updated: 2020-07-14T12:44:42Z has_accepted_license: '1' intvolume: ' 5' issue: 2016JULY language: - iso: eng month: '07' oa: 1 oa_version: Published Version publication: eLife publication_status: published publisher: eLife Sciences Publications publist_id: '6056' pubrep_id: '700' quality_controlled: '1' scopus_import: 1 status: public title: Neural oscillations as a signature of efficient coding in the presence of synaptic delays tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 5 year: '2016' ... --- _id: '1290' abstract: - lang: eng text: We developed a competition-based screening strategy to identify compounds that invert the selective advantage of antibiotic resistance. Using our assay, we screened over 19,000 compounds for the ability to select against the TetA tetracycline-resistance efflux pump in Escherichia coli and identified two hits, β-thujaplicin and disulfiram. Treating a tetracycline-resistant population with β-thujaplicin selects for loss of the resistance gene, enabling an effective second-phase treatment with doxycycline. acknowledgement: "This work was supported in part by National Institute of Allergy and Infectious Diseases grant U54 AI057159, US National Institutes of Health grants R01 GM081617 (to R.K.) and GM086258 (to J.C.), European Research Council FP7 ERC grant 281891 (to R.K.) and a National Science Foundation Graduate Fellowship (to L.K.S.).\r\n" author: - first_name: Laura full_name: Stone, Laura last_name: Stone - first_name: Michael full_name: Baym, Michael last_name: Baym - first_name: Tami full_name: Lieberman, Tami last_name: Lieberman - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Jon full_name: Clardy, Jon last_name: Clardy - first_name: Roy full_name: Kishony, Roy last_name: Kishony citation: ama: Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. 2016;12(11):902-904. doi:10.1038/nchembio.2176 apa: Stone, L., Baym, M., Lieberman, T., Chait, R. P., Clardy, J., & Kishony, R. (2016). Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. Nature Publishing Group. https://doi.org/10.1038/nchembio.2176 chicago: Stone, Laura, Michael Baym, Tami Lieberman, Remy P Chait, Jon Clardy, and Roy Kishony. “Compounds That Select against the Tetracycline-Resistance Efflux Pump.” Nature Chemical Biology. Nature Publishing Group, 2016. https://doi.org/10.1038/nchembio.2176. ieee: L. Stone, M. Baym, T. Lieberman, R. P. Chait, J. Clardy, and R. Kishony, “Compounds that select against the tetracycline-resistance efflux pump,” Nature Chemical Biology, vol. 12, no. 11. Nature Publishing Group, pp. 902–904, 2016. ista: Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. 2016. Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. 12(11), 902–904. mla: Stone, Laura, et al. “Compounds That Select against the Tetracycline-Resistance Efflux Pump.” Nature Chemical Biology, vol. 12, no. 11, Nature Publishing Group, 2016, pp. 902–04, doi:10.1038/nchembio.2176. short: L. Stone, M. Baym, T. Lieberman, R.P. Chait, J. Clardy, R. Kishony, Nature Chemical Biology 12 (2016) 902–904. date_created: 2018-12-11T11:51:10Z date_published: 2016-11-01T00:00:00Z date_updated: 2021-01-12T06:49:39Z day: '01' department: - _id: CaGu - _id: GaTk doi: 10.1038/nchembio.2176 intvolume: ' 12' issue: '11' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069154/ month: '11' oa: 1 oa_version: Preprint page: 902 - 904 publication: Nature Chemical Biology publication_status: published publisher: Nature Publishing Group publist_id: '6026' quality_controlled: '1' scopus_import: 1 status: public title: Compounds that select against the tetracycline-resistance efflux pump type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 12 year: '2016' ... --- _id: '1320' abstract: - lang: eng text: 'In recent years, several biomolecular systems have been shown to be scale-invariant (SI), i.e. to show the same output dynamics when exposed to geometrically scaled input signals (u → pu, p > 0) after pre-adaptation to accordingly scaled constant inputs. In this article, we show that SI systems-as well as systems invariant with respect to other input transformations-can realize nonlinear differential operators: when excited by inputs obeying functional forms characteristic for a given class of invariant systems, the systems'' outputs converge to constant values directly quantifying the speed of the input.' acknowledgement: The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement n° [291734]. Work supported in part by grants AFOSR FA9550-14-1-0060 and NIH 1R01GM100473. article_number: '7526722' author: - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Eduardo full_name: Sontag, Eduardo last_name: Sontag citation: ama: 'Lang M, Sontag E. Scale-invariant systems realize nonlinear differential operators. In: Vol 2016-July. IEEE; 2016. doi:10.1109/ACC.2016.7526722' apa: 'Lang, M., & Sontag, E. (2016). Scale-invariant systems realize nonlinear differential operators (Vol. 2016–July). Presented at the ACC: American Control Conference, Boston, MA, USA: IEEE. https://doi.org/10.1109/ACC.2016.7526722' chicago: Lang, Moritz, and Eduardo Sontag. “Scale-Invariant Systems Realize Nonlinear Differential Operators,” Vol. 2016–July. IEEE, 2016. https://doi.org/10.1109/ACC.2016.7526722. ieee: 'M. Lang and E. Sontag, “Scale-invariant systems realize nonlinear differential operators,” presented at the ACC: American Control Conference, Boston, MA, USA, 2016, vol. 2016–July.' ista: 'Lang M, Sontag E. 2016. Scale-invariant systems realize nonlinear differential operators. ACC: American Control Conference vol. 2016–July, 7526722.' mla: Lang, Moritz, and Eduardo Sontag. Scale-Invariant Systems Realize Nonlinear Differential Operators. Vol. 2016–July, 7526722, IEEE, 2016, doi:10.1109/ACC.2016.7526722. short: M. Lang, E. Sontag, in:, IEEE, 2016. conference: end_date: 2016-07-08 location: Boston, MA, USA name: 'ACC: American Control Conference' start_date: 2016-07-06 date_created: 2018-12-11T11:51:21Z date_published: 2016-07-28T00:00:00Z date_updated: 2021-01-12T06:49:51Z day: '28' ddc: - '003' - '621' department: - _id: CaGu - _id: GaTk doi: 10.1109/ACC.2016.7526722 ec_funded: 1 file: - access_level: local checksum: 7219432b43defc62a0d45f48d4ce6a19 content_type: application/pdf creator: system date_created: 2018-12-12T10:16:17Z date_updated: 2020-07-14T12:44:43Z file_id: '5203' file_name: IST-2017-810-v1+1_root.pdf file_size: 539166 relation: main_file file_date_updated: 2020-07-14T12:44:43Z has_accepted_license: '1' language: - iso: eng month: '07' oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication_status: published publisher: IEEE publist_id: '5950' pubrep_id: '810' quality_controlled: '1' scopus_import: 1 status: public title: Scale-invariant systems realize nonlinear differential operators type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 2016-July year: '2016' ... --- _id: '1332' abstract: - lang: eng text: Antibiotic-sensitive and -resistant bacteria coexist in natural environments with low, if detectable, antibiotic concentrations. Except possibly around localized antibiotic sources, where resistance can provide a strong advantage, bacterial fitness is dominated by stresses unaffected by resistance to the antibiotic. How do such mixed and heterogeneous conditions influence the selective advantage or disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels of tetracyclines potentiate selection for or against tetracycline resistance around localized sources of almost any toxin or stress. Furthermore, certain stresses generate alternating rings of selection for and against resistance around a localized source of the antibiotic. In these conditions, localized antibiotic sources, even at high strengths, can actually produce a net selection against resistance to the antibiotic. Our results show that interactions between the effects of an antibiotic and other stresses in inhomogeneous environments can generate pervasive, complex patterns of selection both for and against antibiotic resistance. acknowledgement: This work was partially supported by US National Institutes of Health grant R01-GM081617, Israeli Centers of Research Excellence I-CORE Program ISF Grant No. 152/11, and the European Research Council FP7 ERC Grant 281891. article_number: '10333' author: - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Adam full_name: Palmer, Adam last_name: Palmer - first_name: Idan full_name: Yelin, Idan last_name: Yelin - first_name: Roy full_name: Kishony, Roy last_name: Kishony citation: ama: Chait RP, Palmer A, Yelin I, Kishony R. Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. 2016;7. doi:10.1038/ncomms10333 apa: Chait, R. P., Palmer, A., Yelin, I., & Kishony, R. (2016). Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms10333 chicago: Chait, Remy P, Adam Palmer, Idan Yelin, and Roy Kishony. “Pervasive Selection for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms10333. ieee: R. P. Chait, A. Palmer, I. Yelin, and R. Kishony, “Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments,” Nature Communications, vol. 7. Nature Publishing Group, 2016. ista: Chait RP, Palmer A, Yelin I, Kishony R. 2016. Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. 7, 10333. mla: Chait, Remy P., et al. “Pervasive Selection for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.” Nature Communications, vol. 7, 10333, Nature Publishing Group, 2016, doi:10.1038/ncomms10333. short: R.P. Chait, A. Palmer, I. Yelin, R. Kishony, Nature Communications 7 (2016). date_created: 2018-12-11T11:51:25Z date_published: 2016-01-20T00:00:00Z date_updated: 2021-01-12T06:49:57Z day: '20' ddc: - '570' - '579' department: - _id: CaGu - _id: GaTk doi: 10.1038/ncomms10333 file: - access_level: open_access checksum: ef147bcbb8bd37e9079cf3ce06f5815d content_type: application/pdf creator: system date_created: 2018-12-12T10:13:52Z date_updated: 2020-07-14T12:44:44Z file_id: '5039' file_name: IST-2016-662-v1+1_ncomms10333.pdf file_size: 1844107 relation: main_file file_date_updated: 2020-07-14T12:44:44Z has_accepted_license: '1' intvolume: ' 7' language: - iso: eng month: '01' oa: 1 oa_version: Published Version publication: Nature Communications publication_status: published publisher: Nature Publishing Group publist_id: '5936' pubrep_id: '662' quality_controlled: '1' scopus_import: 1 status: public title: Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 7 year: '2016' ... --- _id: '1342' abstract: - lang: eng text: A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front.While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front,we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behindmore sensitive lineages.TheMEGA-plate provides a versatile platformfor studying microbial adaption and directly visualizing evolutionary dynamics. author: - first_name: Michael full_name: Baym, Michael last_name: Baym - first_name: Tami full_name: Lieberman, Tami last_name: Lieberman - first_name: Eric full_name: Kelsic, Eric last_name: Kelsic - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Rotem full_name: Gross, Rotem last_name: Gross - first_name: Idan full_name: Yelin, Idan last_name: Yelin - first_name: Roy full_name: Kishony, Roy last_name: Kishony citation: ama: Baym M, Lieberman T, Kelsic E, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016;353(6304):1147-1151. doi:10.1126/science.aag0822 apa: Baym, M., Lieberman, T., Kelsic, E., Chait, R. P., Gross, R., Yelin, I., & Kishony, R. (2016). Spatiotemporal microbial evolution on antibiotic landscapes. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aag0822 chicago: Baym, Michael, Tami Lieberman, Eric Kelsic, Remy P Chait, Rotem Gross, Idan Yelin, and Roy Kishony. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.” Science. American Association for the Advancement of Science, 2016. https://doi.org/10.1126/science.aag0822. ieee: M. Baym et al., “Spatiotemporal microbial evolution on antibiotic landscapes,” Science, vol. 353, no. 6304. American Association for the Advancement of Science, pp. 1147–1151, 2016. ista: Baym M, Lieberman T, Kelsic E, Chait RP, Gross R, Yelin I, Kishony R. 2016. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 353(6304), 1147–1151. mla: Baym, Michael, et al. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.” Science, vol. 353, no. 6304, American Association for the Advancement of Science, 2016, pp. 1147–51, doi:10.1126/science.aag0822. short: M. Baym, T. Lieberman, E. Kelsic, R.P. Chait, R. Gross, I. Yelin, R. Kishony, Science 353 (2016) 1147–1151. date_created: 2018-12-11T11:51:29Z date_published: 2016-09-09T00:00:00Z date_updated: 2021-01-12T06:50:01Z day: '09' department: - _id: CaGu - _id: GaTk doi: 10.1126/science.aag0822 intvolume: ' 353' issue: '6304' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5534434/ month: '09' oa: 1 oa_version: Preprint page: 1147 - 1151 publication: Science publication_status: published publisher: American Association for the Advancement of Science publist_id: '5911' quality_controlled: '1' scopus_import: 1 status: public title: Spatiotemporal microbial evolution on antibiotic landscapes type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 353 year: '2016' ... --- _id: '1394' abstract: - lang: eng text: "The solution space of genome-scale models of cellular metabolism provides a map between physically\r\nviable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the\r\ncorresponding growth rates. By sampling the solution space of E. coliʼs metabolic network, we show\r\nthat empirical growth rate distributions recently obtained in experiments at single-cell resolution can\r\nbe explained in terms of a trade-off between the higher fitness of fast-growing phenotypes and the\r\nhigher entropy of slow-growing ones. Based on this, we propose a minimal model for the evolution of\r\na large bacterial population that captures this trade-off. The scaling relationships observed in\r\nexperiments encode, in such frameworks, for the same distance from the maximum achievable growth\r\nrate, the same degree of growth rate maximization, and/or the same rate of phenotypic change. Being\r\ngrounded on genome-scale metabolic network reconstructions, these results allow for multiple\r\nimplications and extensions in spite of the underlying conceptual simplicity." acknowledgement: "The research leading to these results has received funding from the from the Marie\r\nCurie Action ITN NETADIS, grant agreement no. 290038." article_number: '036005' author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Fabrizio full_name: Capuani, Fabrizio last_name: Capuani - first_name: Andrea full_name: De Martino, Andrea last_name: De Martino citation: ama: 'De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005' apa: 'De Martino, D., Capuani, F., & De Martino, A. (2016). Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/3/036005' chicago: 'De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/3/036005.' ieee: 'D. De Martino, F. Capuani, and A. De Martino, “Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli,” Physical Biology, vol. 13, no. 3. IOP Publishing Ltd., 2016.' ista: 'De Martino D, Capuani F, De Martino A. 2016. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 13(3), 036005.' mla: 'De Martino, Daniele, et al. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology, vol. 13, no. 3, 036005, IOP Publishing Ltd., 2016, doi:10.1088/1478-3975/13/3/036005.' short: D. De Martino, F. Capuani, A. De Martino, Physical Biology 13 (2016). date_created: 2018-12-11T11:51:46Z date_published: 2016-05-27T00:00:00Z date_updated: 2021-01-12T06:50:23Z day: '27' department: - _id: GaTk doi: 10.1088/1478-3975/13/3/036005 ec_funded: 1 intvolume: ' 13' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1601.03243 month: '05' oa: 1 oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Physical Biology publication_status: published publisher: IOP Publishing Ltd. publist_id: '5815' quality_controlled: '1' scopus_import: 1 status: public title: 'Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli' type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2016' ... --- _id: '1420' abstract: - lang: eng text: 'Selection, mutation, and random drift affect the dynamics of allele frequencies and consequently of quantitative traits. While the macroscopic dynamics of quantitative traits can be measured, the underlying allele frequencies are typically unobserved. Can we understand how the macroscopic observables evolve without following these microscopic processes? This problem has been studied previously by analogy with statistical mechanics: the allele frequency distribution at each time point is approximated by the stationary form, which maximizes entropy. We explore the limitations of this method when mutation is small (4Nμ < 1) so that populations are typically close to fixation, and we extend the theory in this regime to account for changes in mutation strength. We consider a single diallelic locus either under directional selection or with overdominance and then generalize to multiple unlinked biallelic loci with unequal effects. We find that the maximum-entropy approximation is remarkably accurate, even when mutation and selection change rapidly. ' article_processing_charge: No author: - first_name: Katarína full_name: Bod'ová, Katarína id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bod'ová orcid: 0000-0002-7214-0171 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 citation: ama: Bodova K, Tkačik G, Barton NH. A general approximation for the dynamics of quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127 apa: Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation for the dynamics of quantitative traits. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.184127 chicago: Bodova, Katarina, Gašper Tkačik, and Nicholas H Barton. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.184127. ieee: K. Bodova, G. Tkačik, and N. H. Barton, “A general approximation for the dynamics of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of America, pp. 1523–1548, 2016. ista: Bodova K, Tkačik G, Barton NH. 2016. A general approximation for the dynamics of quantitative traits. Genetics. 202(4), 1523–1548. mla: Bodova, Katarina, et al. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics, vol. 202, no. 4, Genetics Society of America, 2016, pp. 1523–48, doi:10.1534/genetics.115.184127. short: K. Bodova, G. Tkačik, N.H. Barton, Genetics 202 (2016) 1523–1548. date_created: 2018-12-11T11:51:55Z date_published: 2016-04-06T00:00:00Z date_updated: 2022-08-01T10:49:55Z day: '06' department: - _id: GaTk - _id: NiBa doi: 10.1534/genetics.115.184127 ec_funded: 1 external_id: arxiv: - '1510.08344' intvolume: ' 202' issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1510.08344 month: '04' oa: 1 oa_version: Preprint page: 1523 - 1548 project: - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation - _id: 255008E4-B435-11E9-9278-68D0E5697425 grant_number: RGP0065/2012 name: Information processing and computation in fish groups publication: Genetics publication_status: published publisher: Genetics Society of America publist_id: '5787' quality_controlled: '1' scopus_import: '1' status: public title: A general approximation for the dynamics of quantitative traits type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 202 year: '2016' ... --- _id: '1485' abstract: - lang: eng text: In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism. article_number: '016003' author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: De Martino D. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 2016;13(1). doi:10.1088/1478-3975/13/1/016003 apa: De Martino, D. (2016). Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/1/016003 chicago: De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/1/016003. ieee: D. De Martino, “Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis,” Physical Biology, vol. 13, no. 1. IOP Publishing Ltd., 2016. ista: De Martino D. 2016. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 13(1), 016003. mla: De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology, vol. 13, no. 1, 016003, IOP Publishing Ltd., 2016, doi:10.1088/1478-3975/13/1/016003. short: D. De Martino, Physical Biology 13 (2016). date_created: 2018-12-11T11:52:18Z date_published: 2016-01-29T00:00:00Z date_updated: 2021-01-12T06:51:04Z day: '29' department: - _id: GaTk doi: 10.1088/1478-3975/13/1/016003 ec_funded: 1 intvolume: ' 13' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1505.04613 month: '01' oa: 1 oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Physical Biology publication_status: published publisher: IOP Publishing Ltd. publist_id: '5702' quality_controlled: '1' scopus_import: 1 status: public title: Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2016' ... --- _id: '1148' abstract: - lang: eng text: Continuous-time Markov chain (CTMC) models have become a central tool for understanding the dynamics of complex reaction networks and the importance of stochasticity in the underlying biochemical processes. When such models are employed to answer questions in applications, in order to ensure that the model provides a sufficiently accurate representation of the real system, it is of vital importance that the model parameters are inferred from real measured data. This, however, is often a formidable task and all of the existing methods fail in one case or the other, usually because the underlying CTMC model is high-dimensional and computationally difficult to analyze. The parameter inference methods that tend to scale best in the dimension of the CTMC are based on so-called moment closure approximations. However, there exists a large number of different moment closure approximations and it is typically hard to say a priori which of the approximations is the most suitable for the inference procedure. Here, we propose a moment-based parameter inference method that automatically chooses the most appropriate moment closure method. Accordingly, contrary to existing methods, the user is not required to be experienced in moment closure techniques. In addition to that, our method adaptively changes the approximation during the parameter inference to ensure that always the best approximation is used, even in cases where different approximations are best in different regions of the parameter space. © 2016 Elsevier Ireland Ltd acknowledgement: This work is based on the CMSB 2015 paper “Adaptive moment closure for parameter inference of biochemical reaction networks” (Bogomolov et al., 2015). The work was partly supported by the German Research Foundation (DFG) as part of the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS1), by the European Research Council (ERC) under grant 267989 (QUAREM) and by the Austrian Science Fund (FWF) under grants S11402-N23 (RiSE) and Z211-N23 (Wittgenstein Award). J.R. acknowledges support from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. 291734. author: - first_name: Christian full_name: Schilling, Christian last_name: Schilling - first_name: Sergiy full_name: Bogomolov, Sergiy id: 369D9A44-F248-11E8-B48F-1D18A9856A87 last_name: Bogomolov orcid: 0000-0002-0686-0365 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000−0002−2985−7724 - first_name: Andreas full_name: Podelski, Andreas last_name: Podelski - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 citation: ama: Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. 2016;149:15-25. doi:10.1016/j.biosystems.2016.07.005 apa: Schilling, C., Bogomolov, S., Henzinger, T. A., Podelski, A., & Ruess, J. (2016). Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. Elsevier. https://doi.org/10.1016/j.biosystems.2016.07.005 chicago: Schilling, Christian, Sergiy Bogomolov, Thomas A Henzinger, Andreas Podelski, and Jakob Ruess. “Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks.” Biosystems. Elsevier, 2016. https://doi.org/10.1016/j.biosystems.2016.07.005. ieee: C. Schilling, S. Bogomolov, T. A. Henzinger, A. Podelski, and J. Ruess, “Adaptive moment closure for parameter inference of biochemical reaction networks,” Biosystems, vol. 149. Elsevier, pp. 15–25, 2016. ista: Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. 2016. Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. 149, 15–25. mla: Schilling, Christian, et al. “Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks.” Biosystems, vol. 149, Elsevier, 2016, pp. 15–25, doi:10.1016/j.biosystems.2016.07.005. short: C. Schilling, S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, Biosystems 149 (2016) 15–25. date_created: 2018-12-11T11:50:24Z date_published: 2016-11-01T00:00:00Z date_updated: 2023-02-23T10:08:46Z day: '01' department: - _id: ToHe - _id: GaTk doi: 10.1016/j.biosystems.2016.07.005 ec_funded: 1 intvolume: ' 149' language: - iso: eng month: '11' oa_version: None page: 15 - 25 project: - _id: 25EE3708-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '267989' name: Quantitative Reactive Modeling - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Biosystems publication_status: published publisher: Elsevier publist_id: '6210' quality_controlled: '1' related_material: record: - id: '1658' relation: earlier_version status: public scopus_import: 1 status: public title: Adaptive moment closure for parameter inference of biochemical reaction networks type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 149 year: '2016' ... --- _id: '8094' abstract: - lang: eng text: 'With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. The idea is that the controller controls the world---the body plus its environment---as reliably as possible. This paper focuses on new lines of self-organization for developmental robotics. We apply the recently developed differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object''s internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently discovers how to rotate it. In this way, the robot discovers affordances of objects its body is interacting with.' article_processing_charge: No author: - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius - first_name: Rafael full_name: Hostettler, Rafael last_name: Hostettler - first_name: Alois full_name: Knoll, Alois last_name: Knoll - first_name: Ralf full_name: Der, Ralf last_name: Der citation: ama: 'Martius GS, Hostettler R, Knoll A, Der R. Self-organized control of an tendon driven arm by differential extrinsic plasticity. In: Proceedings of the Artificial Life Conference 2016. Vol 28. MIT Press; 2016:142-143. doi:10.7551/978-0-262-33936-0-ch029' apa: 'Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Self-organized control of an tendon driven arm by differential extrinsic plasticity. In Proceedings of the Artificial Life Conference 2016 (Vol. 28, pp. 142–143). Cancun, Mexico: MIT Press. https://doi.org/10.7551/978-0-262-33936-0-ch029' chicago: Martius, Georg S, Rafael Hostettler, Alois Knoll, and Ralf Der. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.” In Proceedings of the Artificial Life Conference 2016, 28:142–43. MIT Press, 2016. https://doi.org/10.7551/978-0-262-33936-0-ch029. ieee: G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Self-organized control of an tendon driven arm by differential extrinsic plasticity,” in Proceedings of the Artificial Life Conference 2016, Cancun, Mexico, 2016, vol. 28, pp. 142–143. ista: 'Martius GS, Hostettler R, Knoll A, Der R. 2016. Self-organized control of an tendon driven arm by differential extrinsic plasticity. Proceedings of the Artificial Life Conference 2016. ALIFE 2016: 15th International Conference on the Synthesis and Simulation of Living Systems vol. 28, 142–143.' mla: Martius, Georg S., et al. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.” Proceedings of the Artificial Life Conference 2016, vol. 28, MIT Press, 2016, pp. 142–43, doi:10.7551/978-0-262-33936-0-ch029. short: G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, Proceedings of the Artificial Life Conference 2016, MIT Press, 2016, pp. 142–143. conference: end_date: 2016-07-08 location: Cancun, Mexico name: 'ALIFE 2016: 15th International Conference on the Synthesis and Simulation of Living Systems' start_date: 2016-07-04 date_created: 2020-07-05T22:00:47Z date_published: 2016-09-01T00:00:00Z date_updated: 2021-01-12T08:16:53Z day: '01' ddc: - '610' department: - _id: ChLa - _id: GaTk doi: 10.7551/978-0-262-33936-0-ch029 ec_funded: 1 file: - access_level: open_access checksum: cff63e7a4b8ac466ba51a9c84153a940 content_type: application/pdf creator: cziletti date_created: 2020-07-06T12:59:09Z date_updated: 2020-07-14T12:48:09Z file_id: '8096' file_name: 2016_ProcALIFE_Martius.pdf file_size: 678670 relation: main_file file_date_updated: 2020-07-14T12:48:09Z has_accepted_license: '1' intvolume: ' 28' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: 142-143 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Proceedings of the Artificial Life Conference 2016 publication_identifier: isbn: - '9780262339360' publication_status: published publisher: MIT Press quality_controlled: '1' scopus_import: 1 status: public title: Self-organized control of an tendon driven arm by differential extrinsic plasticity tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: D865714E-FA4E-11E9-B85B-F5C5E5697425 volume: 28 year: '2016' ... --- _id: '1197' abstract: - lang: eng text: Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells’ collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina. acknowledgement: JSP was supported by a C.V. Starr Fellowship from the Starr Foundation (http://www.starrfoundation.org/). GT was supported by Austrian Research Foundation (https://www.fwf.ac.at/en/) grant FWF P25651. MJB received support from National Eye Institute (https://nei.nih.gov/) grant EY 14196 and from the National Science Foundation grant 1504977. The authors thank Cristina Savin and Vicent Botella-Soler for helpful comments on the manuscript. article_number: e1005855 author: - first_name: Jason full_name: Prentice, Jason last_name: Prentice - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Mark full_name: Ioffe, Mark last_name: Ioffe - first_name: Adrianna full_name: Loback, Adrianna last_name: Loback - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Michael full_name: Berry, Michael last_name: Berry citation: ama: Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. Error-robust modes of the retinal population code. PLoS Computational Biology. 2016;12(11). doi:10.1371/journal.pcbi.1005148 apa: Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M. (2016). Error-robust modes of the retinal population code. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005148 chicago: Prentice, Jason, Olivier Marre, Mark Ioffe, Adrianna Loback, Gašper Tkačik, and Michael Berry. “Error-Robust Modes of the Retinal Population Code.” PLoS Computational Biology. Public Library of Science, 2016. https://doi.org/10.1371/journal.pcbi.1005148. ieee: J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, and M. Berry, “Error-robust modes of the retinal population code,” PLoS Computational Biology, vol. 12, no. 11. Public Library of Science, 2016. ista: Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. 2016. Error-robust modes of the retinal population code. PLoS Computational Biology. 12(11), e1005855. mla: Prentice, Jason, et al. “Error-Robust Modes of the Retinal Population Code.” PLoS Computational Biology, vol. 12, no. 11, e1005855, Public Library of Science, 2016, doi:10.1371/journal.pcbi.1005148. short: J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, M. Berry, PLoS Computational Biology 12 (2016). date_created: 2018-12-11T11:50:40Z date_published: 2016-11-17T00:00:00Z date_updated: 2023-02-23T14:05:40Z day: '17' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1005148 file: - access_level: open_access checksum: 47b08cbd4dbf32b25ba161f5f4b262cc content_type: application/pdf creator: kschuh date_created: 2019-01-25T10:35:00Z date_updated: 2020-07-14T12:44:38Z file_id: '5884' file_name: 2016_PLOS_Prentice.pdf file_size: 4492021 relation: main_file file_date_updated: 2020-07-14T12:44:38Z has_accepted_license: '1' intvolume: ' 12' issue: '11' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science publist_id: '6153' quality_controlled: '1' related_material: record: - id: '9709' relation: research_data status: public scopus_import: 1 status: public title: Error-robust modes of the retinal population code tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 12 year: '2016' ... --- _id: '948' abstract: - lang: eng text: Experience constantly shapes neural circuits through a variety of plasticity mechanisms. While the functional roles of some plasticity mechanisms are well-understood, it remains unclear how changes in neural excitability contribute to learning. Here, we develop a normative interpretation of intrinsic plasticity (IP) as a key component of unsupervised learning. We introduce a novel generative mixture model that accounts for the class-specific statistics of stimulus intensities, and we derive a neural circuit that learns the input classes and their intensities. We will analytically show that inference and learning for our generative model can be achieved by a neural circuit with intensity-sensitive neurons equipped with a specific form of IP. Numerical experiments verify our analytical derivations and show robust behavior for artificial and natural stimuli. Our results link IP to non-trivial input statistics, in particular the statistics of stimulus intensities for classes to which a neuron is sensitive. More generally, our work paves the way toward new classification algorithms that are robust to intensity variations. acknowledgement: DFG Cluster of Excellence EXC 1077/1 (Hearing4all) and LU 1196/5-1 (JL and TM), People Programme (Marie Curie Actions) FP7/2007-2013 grant agreement no. 291734 (CS) alternative_title: - Advances in Neural Information Processing Systems author: - first_name: Travis full_name: Monk, Travis last_name: Monk - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Jörg full_name: Lücke, Jörg last_name: Lücke citation: ama: 'Monk T, Savin C, Lücke J. Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. In: Vol 29. Neural Information Processing Systems; 2016:4285-4293.' apa: 'Monk, T., Savin, C., & Lücke, J. (2016). Neurons equipped with intrinsic plasticity learn stimulus intensity statistics (Vol. 29, pp. 4285–4293). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine: Neural Information Processing Systems.' chicago: Monk, Travis, Cristina Savin, and Jörg Lücke. “Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics,” 29:4285–93. Neural Information Processing Systems, 2016. ieee: 'T. Monk, C. Savin, and J. Lücke, “Neurons equipped with intrinsic plasticity learn stimulus intensity statistics,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine, 2016, vol. 29, pp. 4285–4293.' ista: 'Monk T, Savin C, Lücke J. 2016. Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 4285–4293.' mla: Monk, Travis, et al. Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics. Vol. 29, Neural Information Processing Systems, 2016, pp. 4285–93. short: T. Monk, C. Savin, J. Lücke, in:, Neural Information Processing Systems, 2016, pp. 4285–4293. conference: end_date: 2016-12-10 location: Barcelona, Spaine name: 'NIPS: Neural Information Processing Systems' start_date: 2016-12-05 date_created: 2018-12-11T11:49:21Z date_published: 2016-01-01T00:00:00Z date_updated: 2021-01-12T08:22:08Z day: '01' department: - _id: GaTk ec_funded: 1 intvolume: ' 29' language: - iso: eng main_file_link: - url: https://papers.nips.cc/paper/6582-neurons-equipped-with-intrinsic-plasticity-learn-stimulus-intensity-statistics month: '01' oa_version: None page: 4285 - 4293 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication_status: published publisher: Neural Information Processing Systems publist_id: '6469' quality_controlled: '1' scopus_import: 1 status: public title: Neurons equipped with intrinsic plasticity learn stimulus intensity statistics type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 29 year: '2016' ... --- _id: '1270' abstract: - lang: eng text: A crucial step in the early development of multicellular organisms involves the establishment of spatial patterns of gene expression which later direct proliferating cells to take on different cell fates. These patterns enable the cells to infer their global position within a tissue or an organism by reading out local gene expression levels. The patterning system is thus said to encode positional information, a concept that was formalized recently in the framework of information theory. Here we introduce a toy model of patterning in one spatial dimension, which can be seen as an extension of Wolpert's paradigmatic "French Flag" model, to patterning by several interacting, spatially coupled genes subject to intrinsic and extrinsic noise. Our model, a variant of an Ising spin system, allows us to systematically explore expression patterns that optimally encode positional information. We find that optimal patterning systems use positional cues, as in the French Flag model, together with gene-gene interactions to generate combinatorial codes for position which we call "Counter" patterns. Counter patterns can also be stabilized against noise and variations in system size or morphogen dosage by longer-range spatial interactions of the type invoked in the Turing model. The simple setup proposed here qualitatively captures many of the experimentally observed properties of biological patterning systems and allows them to be studied in a single, theoretically consistent framework. acknowledgement: The authors would like to thank Thomas Sokolowski and Filipe Tostevin for helpful discussions. PH and UG were funded by the German Excellence Initiative via the program "Nanosystems Initiative Munich" (https://www.nano-initiative-munich.de) and the German Research Foundation via the SFB 1032 "Nanoagents for Spatiotemporal Control of Molecular and Cellular Reactions" (http://www.sfb1032.physik.uni-muenchen.de). GT was funded by the Austrian Science Fund (FWF P 28844) (http://www.fwf.ac.at). article_number: e0163628 author: - first_name: Patrick full_name: Hillenbrand, Patrick last_name: Hillenbrand - first_name: Ulrich full_name: Gerland, Ulrich last_name: Gerland - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: 'Hillenbrand P, Gerland U, Tkačik G. Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. 2016;11(9). doi:10.1371/journal.pone.0163628' apa: 'Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628' chicago: 'Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Beyond the French Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional Information.” PLoS One. Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.' ieee: 'P. Hillenbrand, U. Gerland, and G. Tkačik, “Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information,” PLoS One, vol. 11, no. 9. Public Library of Science, 2016.' ista: 'Hillenbrand P, Gerland U, Tkačik G. 2016. Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. 11(9), e0163628.' mla: 'Hillenbrand, Patrick, et al. “Beyond the French Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional Information.” PLoS One, vol. 11, no. 9, e0163628, Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.' short: P. Hillenbrand, U. Gerland, G. Tkačik, PLoS One 11 (2016). date_created: 2018-12-11T11:51:03Z date_published: 2016-09-27T00:00:00Z date_updated: 2023-02-23T14:11:37Z day: '27' ddc: - '571' department: - _id: GaTk doi: 10.1371/journal.pone.0163628 file: - access_level: open_access checksum: 3d0d55d373096a033bd9cf79288c8586 content_type: application/pdf creator: system date_created: 2018-12-12T10:10:47Z date_updated: 2020-07-14T12:44:42Z file_id: '4837' file_name: IST-2016-696-v1+1_journal.pone.0163628.PDF file_size: 4950415 relation: main_file file_date_updated: 2020-07-14T12:44:42Z has_accepted_license: '1' intvolume: ' 11' issue: '9' language: - iso: eng month: '09' oa: 1 oa_version: Published Version project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: PLoS One publication_status: published publisher: Public Library of Science publist_id: '6050' pubrep_id: '696' quality_controlled: '1' related_material: record: - id: '9869' relation: research_data status: public - id: '9870' relation: research_data status: public - id: '9871' relation: research_data status: public scopus_import: 1 status: public title: 'Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2016' ... --- _id: '9870' abstract: - lang: eng text: The effect of noise in the input field on an Ising model is approximated. Furthermore, methods to compute positional information in an Ising model by transfer matrices and Monte Carlo sampling are outlined. article_processing_charge: No author: - first_name: Patrick full_name: Hillenbrand, Patrick last_name: Hillenbrand - first_name: Ulrich full_name: Gerland, Ulrich last_name: Gerland - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in an Ising model. 2016. doi:10.1371/journal.pone.0163628.s002 apa: Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in an Ising model. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s002 chicago: Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of Positional Information in an Ising Model.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s002. ieee: P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information in an Ising model.” Public Library of Science, 2016. ista: Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information in an Ising model, Public Library of Science, 10.1371/journal.pone.0163628.s002. mla: Hillenbrand, Patrick, et al. Computation of Positional Information in an Ising Model. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s002. short: P. Hillenbrand, U. Gerland, G. Tkačik, (2016). date_created: 2021-08-10T09:23:45Z date_published: 2016-09-27T00:00:00Z date_updated: 2023-02-21T16:56:40Z day: '27' department: - _id: GaTk doi: 10.1371/journal.pone.0163628.s002 month: '09' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1270' relation: used_in_publication status: public status: public title: Computation of positional information in an Ising model type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2016' ... --- _id: '9869' abstract: - lang: eng text: A lower bound on the error of a positional estimator with limited positional information is derived. article_processing_charge: No author: - first_name: Patrick full_name: Hillenbrand, Patrick last_name: Hillenbrand - first_name: Ulrich full_name: Gerland, Ulrich last_name: Gerland - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Hillenbrand P, Gerland U, Tkačik G. Error bound on an estimator of position. 2016. doi:10.1371/journal.pone.0163628.s001 apa: Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Error bound on an estimator of position. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s001 chicago: Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Error Bound on an Estimator of Position.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s001. ieee: P. Hillenbrand, U. Gerland, and G. Tkačik, “Error bound on an estimator of position.” Public Library of Science, 2016. ista: Hillenbrand P, Gerland U, Tkačik G. 2016. Error bound on an estimator of position, Public Library of Science, 10.1371/journal.pone.0163628.s001. mla: Hillenbrand, Patrick, et al. Error Bound on an Estimator of Position. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s001. short: P. Hillenbrand, U. Gerland, G. Tkačik, (2016). date_created: 2021-08-10T08:53:48Z date_published: 2016-09-27T00:00:00Z date_updated: 2023-02-21T16:56:40Z day: '27' department: - _id: GaTk doi: 10.1371/journal.pone.0163628.s001 month: '09' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1270' relation: used_in_publication status: public status: public title: Error bound on an estimator of position type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2016' ... --- _id: '9871' abstract: - lang: eng text: The positional information in a discrete morphogen field with Gaussian noise is computed. article_processing_charge: No author: - first_name: Patrick full_name: Hillenbrand, Patrick last_name: Hillenbrand - first_name: Ulrich full_name: Gerland, Ulrich last_name: Gerland - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in a discrete morphogen field. 2016. doi:10.1371/journal.pone.0163628.s003 apa: Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in a discrete morphogen field. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s003 chicago: Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of Positional Information in a Discrete Morphogen Field.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s003. ieee: P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information in a discrete morphogen field.” Public Library of Science, 2016. ista: Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information in a discrete morphogen field, Public Library of Science, 10.1371/journal.pone.0163628.s003. mla: Hillenbrand, Patrick, et al. Computation of Positional Information in a Discrete Morphogen Field. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s003. short: P. Hillenbrand, U. Gerland, G. Tkačik, (2016). date_created: 2021-08-10T09:27:35Z date_updated: 2023-02-21T16:56:40Z day: '27' department: - _id: GaTk doi: 10.1371/journal.pone.0163628.s003 month: '09' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1270' relation: used_in_publication status: public status: public title: Computation of positional information in a discrete morphogen field type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2016' ... --- _id: '1128' abstract: - lang: eng text: "The process of gene expression is central to the modern understanding of how cellular systems\r\nfunction. In this process, a special kind of regulatory proteins, called transcription factors,\r\nare important to determine how much protein is produced from a given gene. As biological\r\ninformation is transmitted from transcription factor concentration to mRNA levels to amounts of\r\nprotein, various sources of noise arise and pose limits to the fidelity of intracellular signaling.\r\nThis thesis concerns itself with several aspects of stochastic gene expression: (i) the mathematical\r\ndescription of complex promoters responsible for the stochastic production of biomolecules,\r\n(ii) fundamental limits to information processing the cell faces due to the interference from multiple\r\nfluctuating signals, (iii) how the presence of gene expression noise influences the evolution\r\nof regulatory sequences, (iv) and tools for the experimental study of origins and consequences\r\nof cell-cell heterogeneity, including an application to bacterial stress response systems." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh citation: ama: Rieckh G. Studying the complexities of transcriptional regulation. 2016. apa: Rieckh, G. (2016). Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria. chicago: Rieckh, Georg. “Studying the Complexities of Transcriptional Regulation.” Institute of Science and Technology Austria, 2016. ieee: G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute of Science and Technology Austria, 2016. ista: Rieckh G. 2016. Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria. mla: Rieckh, Georg. Studying the Complexities of Transcriptional Regulation. Institute of Science and Technology Austria, 2016. short: G. Rieckh, Studying the Complexities of Transcriptional Regulation, Institute of Science and Technology Austria, 2016. date_created: 2018-12-11T11:50:18Z date_published: 2016-08-01T00:00:00Z date_updated: 2023-09-07T11:44:34Z day: '01' ddc: - '570' degree_awarded: PhD department: - _id: GaTk file: - access_level: closed checksum: ec453918c3bf8e6f460fd1156ef7b493 content_type: application/pdf creator: dernst date_created: 2019-08-13T11:46:25Z date_updated: 2019-08-13T11:46:25Z file_id: '6815' file_name: Thesis_Georg_Rieckh_w_signature_page.pdf file_size: 2614660 relation: main_file - access_level: open_access checksum: 51ae398166370d18fd22478b6365c4da content_type: application/pdf creator: dernst date_created: 2020-09-21T11:30:40Z date_updated: 2020-09-21T11:30:40Z file_id: '8542' file_name: Thesis_Georg_Rieckh.pdf file_size: 6096178 relation: main_file success: 1 file_date_updated: 2020-09-21T11:30:40Z has_accepted_license: '1' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: '114' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publist_id: '6232' status: public supervisor: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 title: Studying the complexities of transcriptional regulation type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2016' ... --- _id: '1358' abstract: - lang: eng text: 'Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements.' article_number: '12307' author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307 apa: Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms12307 chicago: Friedlander, Tamar, Roshan Prizak, Calin C Guet, Nicholas H Barton, and Gašper Tkačik. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms12307. ieee: T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic limits to gene regulation by global crosstalk,” Nature Communications, vol. 7. Nature Publishing Group, 2016. ista: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 7, 12307. mla: Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications, vol. 7, 12307, Nature Publishing Group, 2016, doi:10.1038/ncomms12307. short: T. Friedlander, R. Prizak, C.C. Guet, N.H. Barton, G. Tkačik, Nature Communications 7 (2016). date_created: 2018-12-11T11:51:34Z date_published: 2016-08-04T00:00:00Z date_updated: 2023-09-07T12:53:49Z day: '04' ddc: - '576' department: - _id: GaTk - _id: NiBa - _id: CaGu doi: 10.1038/ncomms12307 ec_funded: 1 file: - access_level: open_access checksum: fe3f3a1526d180b29fe691ab11435b78 content_type: application/pdf creator: system date_created: 2018-12-12T10:12:01Z date_updated: 2020-07-14T12:44:46Z file_id: '4919' file_name: IST-2016-627-v1+1_ncomms12307.pdf file_size: 861805 relation: main_file - access_level: open_access checksum: 164864a1a675f3ad80e9917c27aba07f content_type: application/pdf creator: system date_created: 2018-12-12T10:12:02Z date_updated: 2020-07-14T12:44:46Z file_id: '4920' file_name: IST-2016-627-v1+2_ncomms12307-s1.pdf file_size: 1084703 relation: main_file file_date_updated: 2020-07-14T12:44:46Z has_accepted_license: '1' intvolume: ' 7' language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Nature Communications publication_status: published publisher: Nature Publishing Group publist_id: '5887' pubrep_id: '627' quality_controlled: '1' related_material: record: - id: '6071' relation: dissertation_contains status: public scopus_import: 1 status: public title: Intrinsic limits to gene regulation by global crosstalk tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 7 year: '2016' ... --- _id: '10794' abstract: - lang: eng text: Mathematical models are of fundamental importance in the understanding of complex population dynamics. For instance, they can be used to predict the population evolution starting from different initial conditions or to test how a system responds to external perturbations. For this analysis to be meaningful in real applications, however, it is of paramount importance to choose an appropriate model structure and to infer the model parameters from measured data. While many parameter inference methods are available for models based on deterministic ordinary differential equations, the same does not hold for more detailed individual-based models. Here we consider, in particular, stochastic models in which the time evolution of the species abundances is described by a continuous-time Markov chain. These models are governed by a master equation that is typically difficult to solve. Consequently, traditional inference methods that rely on iterative evaluation of parameter likelihoods are computationally intractable. The aim of this paper is to present recent advances in parameter inference for continuous-time Markov chain models, based on a moment closure approximation of the parameter likelihood, and to investigate how these results can help in understanding, and ultimately controlling, complex systems in ecology. Specifically, we illustrate through an agricultural pest case study how parameters of a stochastic individual-based model can be identified from measured data and how the resulting model can be used to solve an optimal control problem in a stochastic setting. In particular, we show how the matter of determining the optimal combination of two different pest control methods can be formulated as a chance constrained optimization problem where the control action is modeled as a state reset, leading to a hybrid system formulation. acknowledgement: "The authors would like to acknowledge contributions from Baptiste Mottet who performed preliminary analysis regarding parameter inference for the considered case study in a student project (Mottet, 2014/2015).\r\nThe research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement No. [291734] and from SystemsX under the project SignalX." article_number: '42' article_processing_charge: No article_type: original author: - first_name: Francesca full_name: Parise, Francesca last_name: Parise - first_name: John full_name: Lygeros, John last_name: Lygeros - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 citation: ama: 'Parise F, Lygeros J, Ruess J. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 2015;3. doi:10.3389/fenvs.2015.00042' apa: 'Parise, F., Lygeros, J., & Ruess, J. (2015). Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. Frontiers. https://doi.org/10.3389/fenvs.2015.00042' chicago: 'Parise, Francesca, John Lygeros, and Jakob Ruess. “Bayesian Inference for Stochastic Individual-Based Models of Ecological Systems: A Pest Control Simulation Study.” Frontiers in Environmental Science. Frontiers, 2015. https://doi.org/10.3389/fenvs.2015.00042.' ieee: 'F. Parise, J. Lygeros, and J. Ruess, “Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study,” Frontiers in Environmental Science, vol. 3. Frontiers, 2015.' ista: 'Parise F, Lygeros J, Ruess J. 2015. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 3, 42.' mla: 'Parise, Francesca, et al. “Bayesian Inference for Stochastic Individual-Based Models of Ecological Systems: A Pest Control Simulation Study.” Frontiers in Environmental Science, vol. 3, 42, Frontiers, 2015, doi:10.3389/fenvs.2015.00042.' short: F. Parise, J. Lygeros, J. Ruess, Frontiers in Environmental Science 3 (2015). date_created: 2022-02-25T11:42:25Z date_published: 2015-06-10T00:00:00Z date_updated: 2022-02-25T11:59:23Z day: '10' ddc: - '000' - '570' department: - _id: ToHe - _id: GaTk doi: 10.3389/fenvs.2015.00042 ec_funded: 1 file: - access_level: open_access checksum: 26c222487564e1be02a11d688d6f769d content_type: application/pdf creator: dernst date_created: 2022-02-25T11:55:26Z date_updated: 2022-02-25T11:55:26Z file_id: '10795' file_name: 2015_FrontiersEnvironmScience_Parise.pdf file_size: 1371201 relation: main_file success: 1 file_date_updated: 2022-02-25T11:55:26Z has_accepted_license: '1' intvolume: ' 3' keyword: - General Environmental Science language: - iso: eng month: '06' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Frontiers in Environmental Science publication_identifier: issn: - 2296-665X publication_status: published publisher: Frontiers quality_controlled: '1' scopus_import: '1' status: public title: 'Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 3 year: '2015' ... --- _id: '1539' abstract: - lang: eng text: 'Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space. ' article_number: '244103' author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 citation: ama: Ruess J. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 2015;143(24). doi:10.1063/1.4937937 apa: Ruess, J. (2015). Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. American Institute of Physics. https://doi.org/10.1063/1.4937937 chicago: Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics. American Institute of Physics, 2015. https://doi.org/10.1063/1.4937937. ieee: J. Ruess, “Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space,” Journal of Chemical Physics, vol. 143, no. 24. American Institute of Physics, 2015. ista: Ruess J. 2015. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 143(24), 244103. mla: Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics, vol. 143, no. 24, 244103, American Institute of Physics, 2015, doi:10.1063/1.4937937. short: J. Ruess, Journal of Chemical Physics 143 (2015). date_created: 2018-12-11T11:52:36Z date_published: 2015-12-22T00:00:00Z date_updated: 2021-01-12T06:51:28Z day: '22' ddc: - '000' department: - _id: ToHe - _id: GaTk doi: 10.1063/1.4937937 ec_funded: 1 file: - access_level: open_access checksum: 838657118ae286463a2b7737319f35ce content_type: application/pdf creator: system date_created: 2018-12-12T10:07:43Z date_updated: 2020-07-14T12:45:01Z file_id: '4641' file_name: IST-2016-593-v1+1_Minimal_moment_equations.pdf file_size: 605355 relation: main_file file_date_updated: 2020-07-14T12:45:01Z has_accepted_license: '1' intvolume: ' 143' issue: '24' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 25EE3708-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '267989' name: Quantitative Reactive Modeling - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Journal of Chemical Physics publication_status: published publisher: American Institute of Physics publist_id: '5632' pubrep_id: '593' quality_controlled: '1' scopus_import: 1 status: public title: Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 143 year: '2015' ... --- _id: '1538' abstract: - lang: eng text: Systems biology rests on the idea that biological complexity can be better unraveled through the interplay of modeling and experimentation. However, the success of this approach depends critically on the informativeness of the chosen experiments, which is usually unknown a priori. Here, we propose a systematic scheme based on iterations of optimal experiment design, flow cytometry experiments, and Bayesian parameter inference to guide the discovery process in the case of stochastic biochemical reaction networks. To illustrate the benefit of our methodology, we apply it to the characterization of an engineered light-inducible gene expression circuit in yeast and compare the performance of the resulting model with models identified from nonoptimal experiments. In particular, we compare the parameter posterior distributions and the precision to which the outcome of future experiments can be predicted. Moreover, we illustrate how the identified stochastic model can be used to determine light induction patterns that make either the average amount of protein or the variability in a population of cells follow a desired profile. Our results show that optimal experiment design allows one to derive models that are accurate enough to precisely predict and regulate the protein expression in heterogeneous cell populations over extended periods of time. acknowledgement: 'J.R., F.P., and J.L. acknowledge support from the European Commission under the Network of Excellence HYCON2 (highly-complex and networked control systems) and SystemsX.ch under the SignalX Project. J.R. acknowledges support from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013 under REA (Research Executive Agency) Grant 291734. M.K. acknowledges support from Human Frontier Science Program Grant RP0061/2011 (www.hfsp.org). ' author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Francesca full_name: Parise, Francesca last_name: Parise - first_name: Andreas full_name: Milias Argeitis, Andreas last_name: Milias Argeitis - first_name: Mustafa full_name: Khammash, Mustafa last_name: Khammash - first_name: John full_name: Lygeros, John last_name: Lygeros citation: ama: Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 2015;112(26):8148-8153. doi:10.1073/pnas.1423947112 apa: Ruess, J., Parise, F., Milias Argeitis, A., Khammash, M., & Lygeros, J. (2015). Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1423947112 chicago: Ruess, Jakob, Francesca Parise, Andreas Milias Argeitis, Mustafa Khammash, and John Lygeros. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1423947112. ieee: J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, and J. Lygeros, “Iterative experiment design guides the characterization of a light-inducible gene expression circuit,” PNAS, vol. 112, no. 26. National Academy of Sciences, pp. 8148–8153, 2015. ista: Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. 2015. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 112(26), 8148–8153. mla: Ruess, Jakob, et al. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS, vol. 112, no. 26, National Academy of Sciences, 2015, pp. 8148–53, doi:10.1073/pnas.1423947112. short: J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, J. Lygeros, PNAS 112 (2015) 8148–8153. date_created: 2018-12-11T11:52:36Z date_published: 2015-06-30T00:00:00Z date_updated: 2021-01-12T06:51:27Z day: '30' department: - _id: ToHe - _id: GaTk doi: 10.1073/pnas.1423947112 ec_funded: 1 external_id: pmid: - '26085136' intvolume: ' 112' issue: '26' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491780/ month: '06' oa: 1 oa_version: Submitted Version page: 8148 - 8153 pmid: 1 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '5633' quality_controlled: '1' scopus_import: 1 status: public title: Iterative experiment design guides the characterization of a light-inducible gene expression circuit type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 112 year: '2015' ... --- _id: '1564' article_number: '145' author: - first_name: Matthieu full_name: Gilson, Matthieu last_name: Gilson - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Friedemann full_name: Zenke, Friedemann last_name: Zenke citation: ama: 'Gilson M, Savin C, Zenke F. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 2015;9(11). doi:10.3389/fncom.2015.00145' apa: 'Gilson, M., Savin, C., & Zenke, F. (2015). Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2015.00145' chicago: 'Gilson, Matthieu, Cristina Savin, and Friedemann Zenke. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience. Frontiers Research Foundation, 2015. https://doi.org/10.3389/fncom.2015.00145.' ieee: 'M. Gilson, C. Savin, and F. Zenke, “Editorial: Emergent neural computation from the interaction of different forms of plasticity,” Frontiers in Computational Neuroscience, vol. 9, no. 11. Frontiers Research Foundation, 2015.' ista: 'Gilson M, Savin C, Zenke F. 2015. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 9(11), 145.' mla: 'Gilson, Matthieu, et al. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience, vol. 9, no. 11, 145, Frontiers Research Foundation, 2015, doi:10.3389/fncom.2015.00145.' short: M. Gilson, C. Savin, F. Zenke, Frontiers in Computational Neuroscience 9 (2015). date_created: 2018-12-11T11:52:45Z date_published: 2015-11-30T00:00:00Z date_updated: 2021-01-12T06:51:37Z day: '30' ddc: - '570' department: - _id: GaTk doi: 10.3389/fncom.2015.00145 ec_funded: 1 file: - access_level: open_access checksum: cea73b6d3ef1579f32da10b82f4de4fd content_type: application/pdf creator: system date_created: 2018-12-12T10:12:09Z date_updated: 2020-07-14T12:45:02Z file_id: '4927' file_name: IST-2016-479-v1+1_fncom-09-00145.pdf file_size: 187038 relation: main_file file_date_updated: 2020-07-14T12:45:02Z has_accepted_license: '1' intvolume: ' 9' issue: '11' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Frontiers in Computational Neuroscience publication_status: published publisher: Frontiers Research Foundation publist_id: '5607' pubrep_id: '479' quality_controlled: '1' scopus_import: 1 status: public title: 'Editorial: Emergent neural computation from the interaction of different forms of plasticity' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 9 year: '2015' ... --- _id: '1570' abstract: - lang: eng text: Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher-level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no systemspecific modifications of the DEP rule. They rather arise from the underlying mechanism of spontaneous symmetry breaking,which is due to the tight brain body environment coupling. The new synaptic rule is biologically plausible and would be an interesting target for neurobiological investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution. author: - first_name: Ralf full_name: Der, Ralf last_name: Der - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius citation: ama: Der R, Martius GS. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 2015;112(45):E6224-E6232. doi:10.1073/pnas.1508400112 apa: Der, R., & Martius, G. S. (2015). Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1508400112 chicago: Der, Ralf, and Georg S Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1508400112. ieee: R. Der and G. S. Martius, “Novel plasticity rule can explain the development of sensorimotor intelligence,” PNAS, vol. 112, no. 45. National Academy of Sciences, pp. E6224–E6232, 2015. ista: Der R, Martius GS. 2015. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 112(45), E6224–E6232. mla: Der, Ralf, and Georg S. Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.” PNAS, vol. 112, no. 45, National Academy of Sciences, 2015, pp. E6224–32, doi:10.1073/pnas.1508400112. short: R. Der, G.S. Martius, PNAS 112 (2015) E6224–E6232. date_created: 2018-12-11T11:52:47Z date_published: 2015-11-10T00:00:00Z date_updated: 2021-01-12T06:51:40Z day: '10' department: - _id: ChLa - _id: GaTk doi: 10.1073/pnas.1508400112 ec_funded: 1 external_id: pmid: - '26504200' intvolume: ' 112' issue: '45' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653169/ month: '11' oa: 1 oa_version: Submitted Version page: E6224 - E6232 pmid: 1 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '5601' quality_controlled: '1' scopus_import: 1 status: public title: Novel plasticity rule can explain the development of sensorimotor intelligence type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 112 year: '2015' ... --- _id: '1658' abstract: - lang: eng text: Continuous-time Markov chain (CTMC) models have become a central tool for understanding the dynamics of complex reaction networks and the importance of stochasticity in the underlying biochemical processes. When such models are employed to answer questions in applications, in order to ensure that the model provides a sufficiently accurate representation of the real system, it is of vital importance that the model parameters are inferred from real measured data. This, however, is often a formidable task and all of the existing methods fail in one case or the other, usually because the underlying CTMC model is high-dimensional and computationally difficult to analyze. The parameter inference methods that tend to scale best in the dimension of the CTMC are based on so-called moment closure approximations. However, there exists a large number of different moment closure approximations and it is typically hard to say a priori which of the approximations is the most suitable for the inference procedure. Here, we propose a moment-based parameter inference method that automatically chooses the most appropriate moment closure method. Accordingly, contrary to existing methods, the user is not required to be experienced in moment closure techniques. In addition to that, our method adaptively changes the approximation during the parameter inference to ensure that always the best approximation is used, even in cases where different approximations are best in different regions of the parameter space. alternative_title: - LNCS author: - first_name: Sergiy full_name: Bogomolov, Sergiy id: 369D9A44-F248-11E8-B48F-1D18A9856A87 last_name: Bogomolov orcid: 0000-0002-0686-0365 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000−0002−2985−7724 - first_name: Andreas full_name: Podelski, Andreas last_name: Podelski - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Christian full_name: Schilling, Christian last_name: Schilling citation: ama: Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. Adaptive moment closure for parameter inference of biochemical reaction networks. 2015;9308:77-89. doi:10.1007/978-3-319-23401-4_8 apa: 'Bogomolov, S., Henzinger, T. A., Podelski, A., Ruess, J., & Schilling, C. (2015). Adaptive moment closure for parameter inference of biochemical reaction networks. Presented at the CMSB: Computational Methods in Systems Biology, Nantes, France: Springer. https://doi.org/10.1007/978-3-319-23401-4_8' chicago: Bogomolov, Sergiy, Thomas A Henzinger, Andreas Podelski, Jakob Ruess, and Christian Schilling. “Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks.” Lecture Notes in Computer Science. Springer, 2015. https://doi.org/10.1007/978-3-319-23401-4_8. ieee: S. Bogomolov, T. A. Henzinger, A. Podelski, J. Ruess, and C. Schilling, “Adaptive moment closure for parameter inference of biochemical reaction networks,” vol. 9308. Springer, pp. 77–89, 2015. ista: Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. 2015. Adaptive moment closure for parameter inference of biochemical reaction networks. 9308, 77–89. mla: Bogomolov, Sergiy, et al. Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks. Vol. 9308, Springer, 2015, pp. 77–89, doi:10.1007/978-3-319-23401-4_8. short: S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, C. Schilling, 9308 (2015) 77–89. conference: end_date: 2015-09-18 location: Nantes, France name: 'CMSB: Computational Methods in Systems Biology' start_date: 2015-09-16 date_created: 2018-12-11T11:53:18Z date_published: 2015-09-01T00:00:00Z date_updated: 2023-02-21T16:17:24Z day: '01' department: - _id: ToHe - _id: GaTk doi: 10.1007/978-3-319-23401-4_8 ec_funded: 1 intvolume: ' 9308' language: - iso: eng month: '09' oa_version: None page: 77 - 89 project: - _id: 25EE3708-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '267989' name: Quantitative Reactive Modeling - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication_status: published publisher: Springer publist_id: '5492' quality_controlled: '1' related_material: record: - id: '1148' relation: later_version status: public scopus_import: 1 series_title: Lecture Notes in Computer Science status: public title: Adaptive moment closure for parameter inference of biochemical reaction networks type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 9308 year: '2015' ... --- _id: '1697' abstract: - lang: eng text: Motion tracking is a challenge the visual system has to solve by reading out the retinal population. It is still unclear how the information from different neurons can be combined together to estimate the position of an object. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bar’s position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. We then took advantage of this unprecedented precision to explore the spatial structure of the retina’s population code. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar’s position. Instead, we found that most ganglion cells in the salamander fired sparsely and idiosyncratically, so that their neural image did not track the bar. Furthermore, ganglion cell activity spanned an area much larger than predicted by their receptive fields, with cells coding for motion far in their surround. As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision. This organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits. acknowledgement: 'This work was supported by grants EY 014196 and EY 017934 to MJB, ANR OPTIMA, the French State program Investissements d’Avenir managed by the Agence Nationale de la Recherche [LIFESENSES: ANR-10-LABX-65], and by a EC grant from the Human Brain Project (CLAP) to OM, the Austrian Research Foundation FWF P25651 to VBS and GT. VBS is partially supported by contracts MEC, Spain (Grant No. AYA2010- 22111-C03-02, Grant No. AYA2013-48623-C2-2 and FEDER Funds).' article_number: e1004304 author: - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Vicente full_name: Botella Soler, Vicente id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: Kristina full_name: Simmons, Kristina last_name: Simmons - first_name: Thierry full_name: Mora, Thierry last_name: Mora - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Michael full_name: Berry, Michael last_name: Berry citation: ama: Marre O, Botella Soler V, Simmons K, Mora T, Tkačik G, Berry M. High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. 2015;11(7). doi:10.1371/journal.pcbi.1004304 apa: Marre, O., Botella Soler, V., Simmons, K., Mora, T., Tkačik, G., & Berry, M. (2015). High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004304 chicago: Marre, Olivier, Vicente Botella Soler, Kristina Simmons, Thierry Mora, Gašper Tkačik, and Michael Berry. “High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.” PLoS Computational Biology. Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004304. ieee: O. Marre, V. Botella Soler, K. Simmons, T. Mora, G. Tkačik, and M. Berry, “High accuracy decoding of dynamical motion from a large retinal population,” PLoS Computational Biology, vol. 11, no. 7. Public Library of Science, 2015. ista: Marre O, Botella Soler V, Simmons K, Mora T, Tkačik G, Berry M. 2015. High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. 11(7), e1004304. mla: Marre, Olivier, et al. “High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.” PLoS Computational Biology, vol. 11, no. 7, e1004304, Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004304. short: O. Marre, V. Botella Soler, K. Simmons, T. Mora, G. Tkačik, M. Berry, PLoS Computational Biology 11 (2015). date_created: 2018-12-11T11:53:31Z date_published: 2015-07-01T00:00:00Z date_updated: 2021-01-12T06:52:35Z day: '01' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004304 file: - access_level: open_access checksum: 472b979f3f1cffb37b3e503f085115ca content_type: application/pdf creator: system date_created: 2018-12-12T10:16:25Z date_updated: 2020-07-14T12:45:12Z file_id: '5212' file_name: IST-2016-455-v1+1_journal.pcbi.1004304.pdf file_size: 4673930 relation: main_file file_date_updated: 2020-07-14T12:45:12Z has_accepted_license: '1' intvolume: ' 11' issue: '7' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science publist_id: '5447' pubrep_id: '455' quality_controlled: '1' scopus_import: 1 status: public title: High accuracy decoding of dynamical motion from a large retinal population tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2015' ... --- _id: '1701' abstract: - lang: eng text: 'The activity of a neural network is defined by patterns of spiking and silence from the individual neurons. Because spikes are (relatively) sparse, patterns of activity with increasing numbers of spikes are less probable, but, with more spikes, the number of possible patterns increases. This tradeoff between probability and numerosity is mathematically equivalent to the relationship between entropy and energy in statistical physics. We construct this relationship for populations of up to N = 160 neurons in a small patch of the vertebrate retina, using a combination of direct and model-based analyses of experiments on the response of this network to naturalistic movies. We see signs of a thermodynamic limit, where the entropy per neuron approaches a smooth function of the energy per neuron as N increases. The form of this function corresponds to the distribution of activity being poised near an unusual kind of critical point. We suggest further tests of criticality, and give a brief discussion of its functional significance. ' acknowledgement: "Research was supported in part by National Science Foundation Grants PHY-1305525, PHY-1451171, and CCF-0939370, by National Institutes of Health Grant R01 EY14196, and by Austrian Science Foundation Grant FWF P25651. Additional support was provided by the\r\nFannie and John Hertz Foundation, by the Swartz Foundation, by the W. M. Keck Foundation, and by the Simons Foundation." author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Thierry full_name: Mora, Thierry last_name: Mora - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Dario full_name: Amodei, Dario last_name: Amodei - first_name: Stephanie full_name: Palmer, Stephanie last_name: Palmer - first_name: Michael full_name: Berry Ii, Michael last_name: Berry Ii - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Tkačik G, Mora T, Marre O, et al. Thermodynamics and signatures of criticality in a network of neurons. PNAS. 2015;112(37):11508-11513. doi:10.1073/pnas.1514188112 apa: Tkačik, G., Mora, T., Marre, O., Amodei, D., Palmer, S., Berry Ii, M., & Bialek, W. (2015). Thermodynamics and signatures of criticality in a network of neurons. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1514188112 chicago: Tkačik, Gašper, Thierry Mora, Olivier Marre, Dario Amodei, Stephanie Palmer, Michael Berry Ii, and William Bialek. “Thermodynamics and Signatures of Criticality in a Network of Neurons.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1514188112. ieee: G. Tkačik et al., “Thermodynamics and signatures of criticality in a network of neurons,” PNAS, vol. 112, no. 37. National Academy of Sciences, pp. 11508–11513, 2015. ista: Tkačik G, Mora T, Marre O, Amodei D, Palmer S, Berry Ii M, Bialek W. 2015. Thermodynamics and signatures of criticality in a network of neurons. PNAS. 112(37), 11508–11513. mla: Tkačik, Gašper, et al. “Thermodynamics and Signatures of Criticality in a Network of Neurons.” PNAS, vol. 112, no. 37, National Academy of Sciences, 2015, pp. 11508–13, doi:10.1073/pnas.1514188112. short: G. Tkačik, T. Mora, O. Marre, D. Amodei, S. Palmer, M. Berry Ii, W. Bialek, PNAS 112 (2015) 11508–11513. date_created: 2018-12-11T11:53:33Z date_published: 2015-09-15T00:00:00Z date_updated: 2021-01-12T06:52:37Z day: '15' department: - _id: GaTk doi: 10.1073/pnas.1514188112 external_id: pmid: - '26330611' intvolume: ' 112' issue: '37' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577210/ month: '09' oa: 1 oa_version: Submitted Version page: 11508 - 11513 pmid: 1 project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '5440' quality_controlled: '1' scopus_import: 1 status: public title: Thermodynamics and signatures of criticality in a network of neurons type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 112 year: '2015' ... --- _id: '1861' abstract: - lang: eng text: Continuous-time Markov chains are commonly used in practice for modeling biochemical reaction networks in which the inherent randomness of themolecular interactions cannot be ignored. This has motivated recent research effort into methods for parameter inference and experiment design for such models. The major difficulty is that such methods usually require one to iteratively solve the chemical master equation that governs the time evolution of the probability distribution of the system. This, however, is rarely possible, and even approximation techniques remain limited to relatively small and simple systems. An alternative explored in this article is to base methods on only some low-order moments of the entire probability distribution. We summarize the theory behind such moment-based methods for parameter inference and experiment design and provide new case studies where we investigate their performance. acknowledgement: "HYCON2; EC; European Commission\r\n" article_number: '8' author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: John full_name: Lygeros, John last_name: Lygeros citation: ama: Ruess J, Lygeros J. Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. 2015;25(2). doi:10.1145/2688906 apa: Ruess, J., & Lygeros, J. (2015). Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. ACM. https://doi.org/10.1145/2688906 chicago: Ruess, Jakob, and John Lygeros. “Moment-Based Methods for Parameter Inference and Experiment Design for Stochastic Biochemical Reaction Networks.” ACM Transactions on Modeling and Computer Simulation. ACM, 2015. https://doi.org/10.1145/2688906. ieee: J. Ruess and J. Lygeros, “Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks,” ACM Transactions on Modeling and Computer Simulation, vol. 25, no. 2. ACM, 2015. ista: Ruess J, Lygeros J. 2015. Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. 25(2), 8. mla: Ruess, Jakob, and John Lygeros. “Moment-Based Methods for Parameter Inference and Experiment Design for Stochastic Biochemical Reaction Networks.” ACM Transactions on Modeling and Computer Simulation, vol. 25, no. 2, 8, ACM, 2015, doi:10.1145/2688906. short: J. Ruess, J. Lygeros, ACM Transactions on Modeling and Computer Simulation 25 (2015). date_created: 2018-12-11T11:54:25Z date_published: 2015-02-01T00:00:00Z date_updated: 2021-01-12T06:53:41Z day: '01' department: - _id: ToHe - _id: GaTk doi: 10.1145/2688906 intvolume: ' 25' issue: '2' language: - iso: eng month: '02' oa_version: None publication: ACM Transactions on Modeling and Computer Simulation publication_status: published publisher: ACM publist_id: '5238' quality_controlled: '1' scopus_import: 1 status: public title: Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 25 year: '2015' ... --- _id: '1885' abstract: - lang: eng text: 'The concept of positional information is central to our understanding of how cells determine their location in a multicellular structure and thereby their developmental fates. Nevertheless, positional information has neither been defined mathematically nor quantified in a principled way. Here we provide an information-theoretic definition in the context of developmental gene expression patterns and examine the features of expression patterns that affect positional information quantitatively. We connect positional information with the concept of positional error and develop tools to directly measure information and error from experimental data. We illustrate our framework for the case of gap gene expression patterns in the early Drosophila embryo and show how information that is distributed among only four genes is sufficient to determine developmental fates with nearly single-cell resolution. Our approach can be generalized to a variety of different model systems; procedures and examples are discussed in detail. ' author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Julien full_name: Dubuis, Julien last_name: Dubuis - first_name: Mariela full_name: Petkova, Mariela last_name: Petkova - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor citation: ama: 'Tkačik G, Dubuis J, Petkova M, Gregor T. Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. 2015;199(1):39-59. doi:10.1534/genetics.114.171850' apa: 'Tkačik, G., Dubuis, J., Petkova, M., & Gregor, T. (2015). Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.114.171850' chicago: 'Tkačik, Gašper, Julien Dubuis, Mariela Petkova, and Thomas Gregor. “Positional Information, Positional Error, and Readout Precision in Morphogenesis: A Mathematical Framework.” Genetics. Genetics Society of America, 2015. https://doi.org/10.1534/genetics.114.171850.' ieee: 'G. Tkačik, J. Dubuis, M. Petkova, and T. Gregor, “Positional information, positional error, and readout precision in morphogenesis: A mathematical framework,” Genetics, vol. 199, no. 1. Genetics Society of America, pp. 39–59, 2015.' ista: 'Tkačik G, Dubuis J, Petkova M, Gregor T. 2015. Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. 199(1), 39–59.' mla: 'Tkačik, Gašper, et al. “Positional Information, Positional Error, and Readout Precision in Morphogenesis: A Mathematical Framework.” Genetics, vol. 199, no. 1, Genetics Society of America, 2015, pp. 39–59, doi:10.1534/genetics.114.171850.' short: G. Tkačik, J. Dubuis, M. Petkova, T. Gregor, Genetics 199 (2015) 39–59. date_created: 2018-12-11T11:54:32Z date_published: 2015-01-01T00:00:00Z date_updated: 2021-01-12T06:53:50Z day: '01' department: - _id: GaTk doi: 10.1534/genetics.114.171850 intvolume: ' 199' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1404.5599 month: '01' oa: 1 oa_version: Preprint page: 39 - 59 publication: Genetics publication_status: published publisher: Genetics Society of America publist_id: '5210' quality_controlled: '1' scopus_import: 1 status: public title: 'Positional information, positional error, and readout precision in morphogenesis: A mathematical framework' type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 199 year: '2015' ... --- _id: '1940' abstract: - lang: eng text: We typically think of cells as responding to external signals independently by regulating their gene expression levels, yet they often locally exchange information and coordinate. Can such spatial coupling be of benefit for conveying signals subject to gene regulatory noise? Here we extend our information-theoretic framework for gene regulation to spatially extended systems. As an example, we consider a lattice of nuclei responding to a concentration field of a transcriptional regulator (the "input") by expressing a single diffusible target gene. When input concentrations are low, diffusive coupling markedly improves information transmission; optimal gene activation functions also systematically change. A qualitatively new regulatory strategy emerges where individual cells respond to the input in a nearly step-like fashion that is subsequently averaged out by strong diffusion. While motivated by early patterning events in the Drosophila embryo, our framework is generically applicable to spatially coupled stochastic gene expression models. article_number: '062710' author: - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Sokolowski TR, Tkačik G. Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2015;91(6). doi:10.1103/PhysRevE.91.062710 apa: Sokolowski, T. R., & Tkačik, G. (2015). Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.91.062710 chicago: Sokolowski, Thomas R, and Gašper Tkačik. “Optimizing Information Flow in Small Genetic Networks. IV. Spatial Coupling.” Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics, 2015. https://doi.org/10.1103/PhysRevE.91.062710. ieee: T. R. Sokolowski and G. Tkačik, “Optimizing information flow in small genetic networks. IV. Spatial coupling,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 91, no. 6. American Institute of Physics, 2015. ista: Sokolowski TR, Tkačik G. 2015. Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. 91(6), 062710. mla: Sokolowski, Thomas R., and Gašper Tkačik. “Optimizing Information Flow in Small Genetic Networks. IV. Spatial Coupling.” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 91, no. 6, 062710, American Institute of Physics, 2015, doi:10.1103/PhysRevE.91.062710. short: T.R. Sokolowski, G. Tkačik, Physical Review E Statistical Nonlinear and Soft Matter Physics 91 (2015). date_created: 2018-12-11T11:54:49Z date_published: 2015-06-15T00:00:00Z date_updated: 2021-01-12T06:54:13Z day: '15' department: - _id: GaTk doi: 10.1103/PhysRevE.91.062710 intvolume: ' 91' issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1501.04015 month: '06' oa: 1 oa_version: Preprint publication: Physical Review E Statistical Nonlinear and Soft Matter Physics publication_status: published publisher: American Institute of Physics publist_id: '5145' quality_controlled: '1' scopus_import: 1 status: public title: Optimizing information flow in small genetic networks. IV. Spatial coupling type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 91 year: '2015' ... --- _id: '9718' article_processing_charge: No author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Avraham E. full_name: Mayo, Avraham E. last_name: Mayo - first_name: Tsvi full_name: Tlusty, Tsvi last_name: Tlusty - first_name: Uri full_name: Alon, Uri last_name: Alon citation: ama: Friedlander T, Mayo AE, Tlusty T, Alon U. Supporting information text. 2015. doi:10.1371/journal.pcbi.1004055.s001 apa: Friedlander, T., Mayo, A. E., Tlusty, T., & Alon, U. (2015). Supporting information text. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055.s001 chicago: Friedlander, Tamar, Avraham E. Mayo, Tsvi Tlusty, and Uri Alon. “Supporting Information Text.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.s001. ieee: T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Supporting information text.” Public Library of Science, 2015. ista: Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Supporting information text, Public Library of Science, 10.1371/journal.pcbi.1004055.s001. mla: Friedlander, Tamar, et al. Supporting Information Text. Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004055.s001. short: T. Friedlander, A.E. Mayo, T. Tlusty, U. Alon, (2015). date_created: 2021-07-26T08:35:23Z date_published: 2015-03-23T00:00:00Z date_updated: 2023-02-23T10:16:13Z day: '23' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004055.s001 month: '03' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1827' relation: used_in_publication status: public status: public title: Supporting information text type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ... --- _id: '1827' abstract: - lang: eng text: Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. article_processing_charge: No author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Avraham full_name: Mayo, Avraham last_name: Mayo - first_name: Tsvi full_name: Tlusty, Tsvi last_name: Tlusty - first_name: Uri full_name: Alon, Uri last_name: Alon citation: ama: Friedlander T, Mayo A, Tlusty T, Alon U. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 2015;11(3). doi:10.1371/journal.pcbi.1004055 apa: Friedlander, T., Mayo, A., Tlusty, T., & Alon, U. (2015). Evolution of bow-tie architectures in biology. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055 chicago: Friedlander, Tamar, Avraham Mayo, Tsvi Tlusty, and Uri Alon. “Evolution of Bow-Tie Architectures in Biology.” PLoS Computational Biology. Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055. ieee: T. Friedlander, A. Mayo, T. Tlusty, and U. Alon, “Evolution of bow-tie architectures in biology,” PLoS Computational Biology, vol. 11, no. 3. Public Library of Science, 2015. ista: Friedlander T, Mayo A, Tlusty T, Alon U. 2015. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 11(3). mla: Friedlander, Tamar, et al. “Evolution of Bow-Tie Architectures in Biology.” PLoS Computational Biology, vol. 11, no. 3, Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004055. short: T. Friedlander, A. Mayo, T. Tlusty, U. Alon, PLoS Computational Biology 11 (2015). date_created: 2018-12-11T11:54:14Z date_published: 2015-03-23T00:00:00Z date_updated: 2023-02-23T14:07:51Z day: '23' ddc: - '576' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004055 ec_funded: 1 file: - access_level: open_access checksum: b8aa66f450ff8de393014b87ec7d2efb content_type: application/pdf creator: system date_created: 2018-12-12T10:15:39Z date_updated: 2020-07-14T12:45:17Z file_id: '5161' file_name: IST-2016-452-v1+1_journal.pcbi.1004055.pdf file_size: 1811647 relation: main_file file_date_updated: 2020-07-14T12:45:17Z has_accepted_license: '1' intvolume: ' 11' issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science publist_id: '5278' pubrep_id: '452' quality_controlled: '1' related_material: record: - id: '9718' relation: research_data status: public - id: '9773' relation: research_data status: public scopus_import: 1 status: public title: Evolution of bow-tie architectures in biology tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2015' ... --- _id: '9773' article_processing_charge: No author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Avraham E. full_name: Mayo, Avraham E. last_name: Mayo - first_name: Tsvi full_name: Tlusty, Tsvi last_name: Tlusty - first_name: Uri full_name: Alon, Uri last_name: Alon citation: ama: Friedlander T, Mayo AE, Tlusty T, Alon U. Evolutionary simulation code. 2015. doi:10.1371/journal.pcbi.1004055.s002 apa: Friedlander, T., Mayo, A. E., Tlusty, T., & Alon, U. (2015). Evolutionary simulation code. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055.s002 chicago: Friedlander, Tamar, Avraham E. Mayo, Tsvi Tlusty, and Uri Alon. “Evolutionary Simulation Code.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.s002. ieee: T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Evolutionary simulation code.” Public Library of Science, 2015. ista: Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Evolutionary simulation code, Public Library of Science, 10.1371/journal.pcbi.1004055.s002. mla: Friedlander, Tamar, et al. Evolutionary Simulation Code. Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004055.s002. short: T. Friedlander, A.E. Mayo, T. Tlusty, U. Alon, (2015). date_created: 2021-08-05T12:58:07Z date_published: 2015-03-23T00:00:00Z date_updated: 2023-02-23T10:16:13Z day: '23' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004055.s002 month: '03' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1827' relation: used_in_publication status: public status: public title: Evolutionary simulation code type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ...