[{"department":[{"_id":"GaTk"}],"month":"08","date_updated":"2026-04-07T12:59:24Z","article_number":"8989292","isi":1,"title":"A tight upper bound on mutual information","citation":{"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.” <i>IEEE Information Theory Workshop, ITW 2019</i>, 8989292, IEEE, 2019, doi:<a href=\"https://doi.org/10.1109/ITW44776.2019.8989292\">10.1109/ITW44776.2019.8989292</a>.","ieee":"M. Hledik, T. R. Sokolowski, and G. Tkačik, “A tight upper bound on mutual information,” in <i>IEEE Information Theory Workshop, ITW 2019</i>, Visby, Sweden, 2019.","apa":"Hledik, M., Sokolowski, T. R., &#38; Tkačik, G. (2019). A tight upper bound on mutual information. In <i>IEEE Information Theory Workshop, ITW 2019</i>. Visby, Sweden: IEEE. <a href=\"https://doi.org/10.1109/ITW44776.2019.8989292\">https://doi.org/10.1109/ITW44776.2019.8989292</a>","short":"M. Hledik, T.R. Sokolowski, G. Tkačik, in:, IEEE Information Theory Workshop, ITW 2019, IEEE, 2019.","chicago":"Hledik, Michal, Thomas R Sokolowski, and Gašper Tkačik. “A Tight Upper Bound on Mutual Information.” In <i>IEEE Information Theory Workshop, ITW 2019</i>. IEEE, 2019. <a href=\"https://doi.org/10.1109/ITW44776.2019.8989292\">https://doi.org/10.1109/ITW44776.2019.8989292</a>.","ama":"Hledik M, Sokolowski TR, Tkačik G. A tight upper bound on mutual information. In: <i>IEEE Information Theory Workshop, ITW 2019</i>. IEEE; 2019. doi:<a href=\"https://doi.org/10.1109/ITW44776.2019.8989292\">10.1109/ITW44776.2019.8989292</a>"},"year":"2019","date_published":"2019-08-01T00:00:00Z","doi":"10.1109/ITW44776.2019.8989292","publication_identifier":{"isbn":["9781538669006"]},"article_processing_charge":"No","publisher":"IEEE","publication_status":"published","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1812.01475"}],"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."}],"conference":{"name":"Information Theory Workshop","end_date":"2019-08-28","start_date":"2019-08-25","location":"Visby, Sweden"},"ec_funded":1,"oa_version":"Preprint","day":"01","project":[{"grant_number":"665385","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program"}],"quality_controlled":"1","external_id":{"arxiv":["1812.01475"],"isi":["000540384500015"]},"type":"conference","author":[{"first_name":"Michal","last_name":"Hledik","id":"4171253A-F248-11E8-B48F-1D18A9856A87","full_name":"Hledik, Michal"},{"id":"3E999752-F248-11E8-B48F-1D18A9856A87","full_name":"Sokolowski, Thomas R","last_name":"Sokolowski","first_name":"Thomas R","orcid":"0000-0002-1287-3779"},{"last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","first_name":"Gašper","orcid":"0000-0002-6699-1455"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","related_material":{"record":[{"status":"public","id":"15020","relation":"dissertation_contains"}]},"oa":1,"arxiv":1,"_id":"7606","status":"public","scopus_import":"1","date_created":"2020-03-22T23:00:47Z","language":[{"iso":"eng"}],"publication":"IEEE Information Theory Workshop, ITW 2019"},{"date_updated":"2026-04-08T13:54:25Z","month":"03","department":[{"_id":"GaTk"},{"_id":"NiBa"}],"title":"Coevolution of transcription factors and their binding sites in sequence space","year":"2019","date_published":"2019-03-11T00:00:00Z","citation":{"short":"R. Prizak, Coevolution of Transcription Factors and Their Binding Sites in Sequence Space, Institute of Science and Technology Austria, 2019.","apa":"Prizak, R. (2019). <i>Coevolution of transcription factors and their binding sites in sequence space</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:th6071\">https://doi.org/10.15479/at:ista:th6071</a>","ama":"Prizak R. Coevolution of transcription factors and their binding sites in sequence space. 2019. doi:<a href=\"https://doi.org/10.15479/at:ista:th6071\">10.15479/at:ista:th6071</a>","chicago":"Prizak, Roshan. “Coevolution of Transcription Factors and Their Binding Sites in Sequence Space.” Institute of Science and Technology Austria, 2019. <a href=\"https://doi.org/10.15479/at:ista:th6071\">https://doi.org/10.15479/at:ista:th6071</a>.","ista":"Prizak R. 2019. Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria.","ieee":"R. Prizak, “Coevolution of transcription factors and their binding sites in sequence space,” Institute of Science and Technology Austria, 2019.","mla":"Prizak, Roshan. <i>Coevolution of Transcription Factors and Their Binding Sites in Sequence Space</i>. Institute of Science and Technology Austria, 2019, doi:<a href=\"https://doi.org/10.15479/at:ista:th6071\">10.15479/at:ista:th6071</a>."},"article_processing_charge":"No","publication_identifier":{"issn":["2663-337X"]},"publisher":"Institute of Science and Technology Austria","doi":"10.15479/at:ista:th6071","publication_status":"published","degree_awarded":"PhD","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. "}],"oa_version":"Published Version","day":"11","alternative_title":["ISTA Thesis"],"project":[{"grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"corr_author":"1","file_date_updated":"2020-07-14T12:47:18Z","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","author":[{"id":"4456104E-F248-11E8-B48F-1D18A9856A87","full_name":"Prizak, Roshan","last_name":"Prizak","first_name":"Roshan"}],"type":"dissertation","related_material":{"record":[{"id":"955","status":"public","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","status":"public","id":"1358"}]},"oa":1,"_id":"6071","OA_place":"publisher","ddc":["576"],"file":[{"date_updated":"2020-07-14T12:47:18Z","file_name":"Thesis_final_PDFA_RoshanPrizak.pdf","content_type":"application/pdf","creator":"rprizak","file_id":"6072","date_created":"2019-03-06T16:05:07Z","checksum":"e60a72de35d270b31f1a23d50f224ec0","access_level":"open_access","file_size":20995465,"relation":"main_file"},{"checksum":"67c2630333d05ebafef5f018863a8465","date_created":"2019-03-06T16:09:39Z","relation":"source_file","file_size":85705272,"access_level":"closed","content_type":"application/zip","file_name":"thesis_v2_merge.zip","date_updated":"2020-07-14T12:47:18Z","file_id":"6073","creator":"rprizak","title":"Latex files"}],"page":"189","date_created":"2019-03-06T16:16:10Z","status":"public","supervisor":[{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","last_name":"Tkačik","first_name":"Gašper","orcid":"0000-0002-6699-1455"}],"language":[{"iso":"eng"}],"has_accepted_license":"1"},{"file":[{"creator":"scepeda","file_id":"6480","content_type":"application/zip","date_updated":"2020-07-14T12:47:31Z","file_name":"Thesis_Cepeda.zip","relation":"source_file","file_size":23937464,"access_level":"closed","checksum":"75f9184c1346e10a5de5f9cc7338309a","date_created":"2019-05-23T11:18:16Z"},{"file_id":"6481","creator":"scepeda","date_updated":"2020-07-14T12:47:31Z","file_name":"CepedaThesis.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file","file_size":16646985,"date_created":"2019-05-23T11:18:13Z","checksum":"afdc0633ddbd71d5b13550d7fb4f4454"}],"ddc":["004"],"page":"135","supervisor":[{"first_name":"Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper"}],"date_created":"2019-05-21T00:11:23Z","status":"public","keyword":["Information estimation","Time-series","data analysis"],"has_accepted_license":"1","language":[{"iso":"eng"}],"file_date_updated":"2020-07-14T12:47:31Z","corr_author":"1","type":"dissertation","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","author":[{"first_name":"Sarah A","last_name":"Cepeda Humerez","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","full_name":"Cepeda Humerez, Sarah A"}],"oa":1,"related_material":{"record":[{"id":"2016","status":"public","relation":"dissertation_contains"},{"status":"public","id":"281","relation":"dissertation_contains"},{"status":"public","id":"1576","relation":"dissertation_contains"},{"relation":"dissertation_contains","status":"public","id":"6900"}]},"OA_place":"publisher","_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. "}],"day":"23","oa_version":"Published Version","alternative_title":["ISTA Thesis"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"department":[{"_id":"GaTk"}],"month":"05","date_updated":"2026-04-16T08:37:38Z","title":"Estimating information flow in single cells","citation":{"apa":"Cepeda Humerez, S. A. (2019). <i>Estimating information flow in single cells</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:6473\">https://doi.org/10.15479/AT:ISTA:6473</a>","short":"S.A. Cepeda Humerez, Estimating Information Flow in Single Cells, Institute of Science and Technology Austria, 2019.","chicago":"Cepeda Humerez, Sarah A. “Estimating Information Flow in Single Cells.” Institute of Science and Technology Austria, 2019. <a href=\"https://doi.org/10.15479/AT:ISTA:6473\">https://doi.org/10.15479/AT:ISTA:6473</a>.","ama":"Cepeda Humerez SA. Estimating information flow in single cells. 2019. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:6473\">10.15479/AT:ISTA:6473</a>","ista":"Cepeda Humerez SA. 2019. Estimating information flow in single cells. Institute of Science and Technology Austria.","mla":"Cepeda Humerez, Sarah A. <i>Estimating Information Flow in Single Cells</i>. Institute of Science and Technology Austria, 2019, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:6473\">10.15479/AT:ISTA:6473</a>.","ieee":"S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute of Science and Technology Austria, 2019."},"year":"2019","date_published":"2019-05-23T00:00:00Z","degree_awarded":"PhD","publication_status":"published","doi":"10.15479/AT:ISTA:6473","article_processing_charge":"No","publisher":"Institute of Science and Technology Austria","publication_identifier":{"issn":["2663-337X"]}},{"type":"journal_article","author":[{"id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","full_name":"Cepeda Humerez, Sarah A","last_name":"Cepeda Humerez","first_name":"Sarah A"},{"full_name":"Ruess, Jakob","last_name":"Ruess","orcid":"0000-0003-1615-3282","first_name":"Jakob"},{"first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","last_name":"Tkačik"}],"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","file_date_updated":"2020-07-14T12:47:44Z","issue":"9","_id":"6900","oa":1,"related_material":{"record":[{"relation":"part_of_dissertation","id":"6473","status":"public"}]},"intvolume":"        15","page":"e1007290","pmid":1,"file":[{"file_size":3081855,"relation":"main_file","access_level":"open_access","checksum":"81bdce1361c9aa8395d6fa635fb6ab47","date_created":"2019-10-01T10:53:45Z","file_id":"6925","creator":"kschuh","content_type":"application/pdf","date_updated":"2020-07-14T12:47:44Z","file_name":"2019_PLoS_Cepeda-Humerez.pdf"}],"ddc":["570"],"has_accepted_license":"1","language":[{"iso":"eng"}],"publication":"PLoS computational biology","status":"public","date_created":"2019-09-22T22:00:37Z","scopus_import":"1","title":"Estimating information in time-varying signals","isi":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"department":[{"_id":"GaTk"}],"month":"09","date_updated":"2026-04-16T08:37:39Z","publication_status":"published","doi":"10.1371/journal.pcbi.1007290","article_processing_charge":"No","publication_identifier":{"eissn":["1553-7358"],"issn":["1553-734X"]},"publisher":"Public Library of Science","citation":{"ista":"Cepeda Humerez SA, Ruess J, Tkačik G. 2019. Estimating information in time-varying signals. PLoS computational biology. 15(9), e1007290.","ieee":"S. A. Cepeda Humerez, J. Ruess, and G. Tkačik, “Estimating information in time-varying signals,” <i>PLoS computational biology</i>, vol. 15, no. 9. Public Library of Science, p. e1007290, 2019.","mla":"Cepeda Humerez, Sarah A., et al. “Estimating Information in Time-Varying Signals.” <i>PLoS Computational Biology</i>, vol. 15, no. 9, Public Library of Science, 2019, p. e1007290, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">10.1371/journal.pcbi.1007290</a>.","short":"S.A. Cepeda Humerez, J. Ruess, G. Tkačik, PLoS Computational Biology 15 (2019) e1007290.","apa":"Cepeda Humerez, S. A., Ruess, J., &#38; Tkačik, G. (2019). Estimating information in time-varying signals. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">https://doi.org/10.1371/journal.pcbi.1007290</a>","ama":"Cepeda Humerez SA, Ruess J, Tkačik G. Estimating information in time-varying signals. <i>PLoS computational biology</i>. 2019;15(9):e1007290. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">10.1371/journal.pcbi.1007290</a>","chicago":"Cepeda Humerez, Sarah A, Jakob Ruess, and Gašper Tkačik. “Estimating Information in Time-Varying Signals.” <i>PLoS Computational Biology</i>. Public Library of Science, 2019. <a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">https://doi.org/10.1371/journal.pcbi.1007290</a>."},"date_published":"2019-09-03T00:00:00Z","year":"2019","abstract":[{"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.","lang":"eng"}],"project":[{"grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"external_id":{"isi":["000489741800021"],"pmid":["31479447"]},"quality_controlled":"1","day":"03","oa_version":"Published Version","volume":15},{"quality_controlled":"1","external_id":{"isi":["000434012100002"]},"project":[{"call_identifier":"H2020","name":"Human Brain Project Specific Grant Agreement 1","_id":"25CBA828-B435-11E9-9278-68D0E5697425","grant_number":"720270"},{"grant_number":"P 25651-N26","call_identifier":"FWF","_id":"254D1A94-B435-11E9-9278-68D0E5697425","name":"Sensitivity to higher-order statistics in natural scenes"}],"ec_funded":1,"day":"10","oa_version":"Published Version","volume":14,"article_type":"original","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."}],"publisher":"Public Library of Science","article_processing_charge":"Yes","doi":"10.1371/journal.pcbi.1006057","publication_status":"published","date_published":"2018-05-10T00:00:00Z","year":"2018","citation":{"ama":"Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. Nonlinear decoding of a complex movie from the mammalian retina. <i>PLoS Computational Biology</i>. 2018;14(5). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1006057\">10.1371/journal.pcbi.1006057</a>","chicago":"Botella Soler, Vicente, Stephane Deny, Georg S Martius, Olivier Marre, and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” <i>PLoS Computational Biology</i>. Public Library of Science, 2018. <a href=\"https://doi.org/10.1371/journal.pcbi.1006057\">https://doi.org/10.1371/journal.pcbi.1006057</a>.","short":"V. Botella Soler, S. Deny, G.S. Martius, O. Marre, G. Tkačik, PLoS Computational Biology 14 (2018).","apa":"Botella Soler, V., Deny, S., Martius, G. S., Marre, O., &#38; Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1006057\">https://doi.org/10.1371/journal.pcbi.1006057</a>","ieee":"V. Botella Soler, S. Deny, G. S. Martius, O. Marre, and G. Tkačik, “Nonlinear decoding of a complex movie from the mammalian retina,” <i>PLoS Computational Biology</i>, vol. 14, no. 5. Public Library of Science, 2018.","mla":"Botella Soler, Vicente, et al. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” <i>PLoS Computational Biology</i>, vol. 14, no. 5, e1006057, Public Library of Science, 2018, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1006057\">10.1371/journal.pcbi.1006057</a>.","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."},"article_number":"e1006057","isi":1,"title":"Nonlinear decoding of a complex movie from the mammalian retina","date_updated":"2025-04-15T08:18:24Z","month":"05","department":[{"_id":"GaTk"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"publication":"PLoS Computational Biology","language":[{"iso":"eng"}],"has_accepted_license":"1","scopus_import":"1","date_created":"2018-12-11T11:45:39Z","status":"public","intvolume":"        14","ddc":["570"],"file":[{"date_created":"2019-02-13T11:07:15Z","checksum":"3026f94d235219e15514505fdbadf34e","access_level":"open_access","file_size":3460786,"relation":"main_file","file_name":"2018_Plos_Botella_Soler.pdf","date_updated":"2020-07-14T12:45:53Z","content_type":"application/pdf","file_id":"5974","creator":"dernst"}],"_id":"292","oa":1,"related_material":{"link":[{"url":"https://ist.ac.at/en/news/video-of-moving-discs-reconstructed-from-rat-retinal-neuron-signals/","description":"News on IST Homepage","relation":"press_release"}],"record":[{"status":"public","id":"5584","relation":"research_data"}]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","author":[{"last_name":"Botella Soler","full_name":"Botella Soler, Vicent","id":"421234E8-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8790-1914","first_name":"Vicent"},{"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","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik"}],"type":"journal_article","issue":"5","file_date_updated":"2020-07-14T12:45:53Z"},{"publisher":"Springer","doi":"10.1007/978-1-4939-7792-5_15","publication_status":"published","year":"2018","date_published":"2018-01-01T00:00:00Z","citation":{"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.” <i>Methods in Molecular Biology</i>, vol. 1771, Springer, 2018, pp. 183–202, doi:<a href=\"https://doi.org/10.1007/978-1-4939-7792-5_15\">10.1007/978-1-4939-7792-5_15</a>.","ieee":"P. Misun, A. Birchler, M. Lang, A. Hierlemann, and O. Frey, “Fabrication and operation of microfluidic hanging drop networks,” <i>Methods in Molecular Biology</i>, vol. 1771. Springer, pp. 183–202, 2018.","apa":"Misun, P., Birchler, A., Lang, M., Hierlemann, A., &#38; Frey, O. (2018). Fabrication and operation of microfluidic hanging drop networks. <i>Methods in Molecular Biology</i>. Springer. <a href=\"https://doi.org/10.1007/978-1-4939-7792-5_15\">https://doi.org/10.1007/978-1-4939-7792-5_15</a>","short":"P. Misun, A. Birchler, M. Lang, A. Hierlemann, O. Frey, Methods in Molecular Biology 1771 (2018) 183–202.","chicago":"Misun, Patrick, Axel Birchler, Moritz Lang, Andreas Hierlemann, and Olivier Frey. “Fabrication and Operation of Microfluidic Hanging Drop Networks.” <i>Methods in Molecular Biology</i>. Springer, 2018. <a href=\"https://doi.org/10.1007/978-1-4939-7792-5_15\">https://doi.org/10.1007/978-1-4939-7792-5_15</a>.","ama":"Misun P, Birchler A, Lang M, Hierlemann A, Frey O. Fabrication and operation of microfluidic hanging drop networks. <i>Methods in Molecular Biology</i>. 2018;1771:183-202. doi:<a href=\"https://doi.org/10.1007/978-1-4939-7792-5_15\">10.1007/978-1-4939-7792-5_15</a>"},"title":"Fabrication and operation of microfluidic hanging drop networks","date_updated":"2021-01-12T07:40:42Z","month":"01","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"alternative_title":["MIMB"],"quality_controlled":"1","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"ec_funded":1,"day":"01","volume":1771,"oa_version":"None","abstract":[{"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.","lang":"eng"}],"_id":"305","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.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Patrick","full_name":"Misun, Patrick","last_name":"Misun"},{"first_name":"Axel","full_name":"Birchler, Axel","last_name":"Birchler"},{"first_name":"Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","full_name":"Lang, Moritz","last_name":"Lang"},{"full_name":"Hierlemann, Andreas","last_name":"Hierlemann","first_name":"Andreas"},{"last_name":"Frey","full_name":"Frey, Olivier","first_name":"Olivier"}],"type":"journal_article","publication":"Methods in Molecular Biology","language":[{"iso":"eng"}],"scopus_import":1,"date_created":"2018-12-11T11:45:43Z","status":"public","publist_id":"7574","intvolume":"      1771","page":"183 - 202"},{"publication":"Heliyon","language":[{"iso":"eng"}],"has_accepted_license":"1","date_created":"2018-12-11T11:45:44Z","scopus_import":1,"status":"public","intvolume":"         4","ddc":["530"],"file":[{"creator":"dernst","file_id":"5929","content_type":"application/pdf","date_updated":"2020-07-14T12:45:59Z","file_name":"2018_Heliyon_DeMartino.pdf","relation":"main_file","file_size":994490,"access_level":"open_access","checksum":"67010cf5e3b3e0637c659371714a715a","date_created":"2019-02-06T07:36:24Z"}],"_id":"306","oa":1,"author":[{"first_name":"Andrea","last_name":"De Martino","full_name":"De Martino, Andrea"},{"last_name":"De Martino","full_name":"De Martino, Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","first_name":"Daniele"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","corr_author":"1","issue":"4","file_date_updated":"2020-07-14T12:45:59Z","quality_controlled":"1","project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734"}],"ec_funded":1,"volume":4,"day":"01","oa_version":"Published Version","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."}],"publisher":"Elsevier","doi":"10.1016/j.heliyon.2018.e00596","publication_status":"published","date_published":"2018-04-01T00:00:00Z","year":"2018","citation":{"mla":"De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” <i>Heliyon</i>, vol. 4, no. 4, e00596, Elsevier, 2018, doi:<a href=\"https://doi.org/10.1016/j.heliyon.2018.e00596\">10.1016/j.heliyon.2018.e00596</a>.","ieee":"A. De Martino and D. De Martino, “An introduction to the maximum entropy approach and its application to inference problems in biology,” <i>Heliyon</i>, 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.","chicago":"De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” <i>Heliyon</i>. Elsevier, 2018. <a href=\"https://doi.org/10.1016/j.heliyon.2018.e00596\">https://doi.org/10.1016/j.heliyon.2018.e00596</a>.","ama":"De Martino A, De Martino D. An introduction to the maximum entropy approach and its application to inference problems in biology. <i>Heliyon</i>. 2018;4(4). doi:<a href=\"https://doi.org/10.1016/j.heliyon.2018.e00596\">10.1016/j.heliyon.2018.e00596</a>","apa":"De Martino, A., &#38; De Martino, D. (2018). An introduction to the maximum entropy approach and its application to inference problems in biology. <i>Heliyon</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.heliyon.2018.e00596\">https://doi.org/10.1016/j.heliyon.2018.e00596</a>","short":"A. De Martino, D. De Martino, Heliyon 4 (2018)."},"article_number":"e00596","title":"An introduction to the maximum entropy approach and its application to inference problems in biology","date_updated":"2024-10-09T20:58:19Z","department":[{"_id":"GaTk"}],"month":"04","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"}},{"citation":{"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.” <i>Physical Review E</i>, vol. 98, no. 4, 042410, American Physical Society, 2018, doi:<a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">10.1103/PhysRevE.98.042410</a>.","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,” <i>Physical Review E</i>, vol. 98, no. 4. American Physical Society, 2018.","apa":"Ferrari, U., Deny, S., Chalk, M. J., Tkačik, G., Marre, O., &#38; Mora, T. (2018). Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. <i>Physical Review E</i>. American Physical Society. <a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">https://doi.org/10.1103/PhysRevE.98.042410</a>","short":"U. Ferrari, S. Deny, M.J. Chalk, G. Tkačik, O. Marre, T. Mora, Physical Review E 98 (2018).","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.” <i>Physical Review E</i>. American Physical Society, 2018. <a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">https://doi.org/10.1103/PhysRevE.98.042410</a>.","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. <i>Physical Review E</i>. 2018;98(4). doi:<a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">10.1103/PhysRevE.98.042410</a>"},"year":"2018","date_published":"2018-10-17T00:00:00Z","publication_status":"published","doi":"10.1103/PhysRevE.98.042410","publisher":"American Physical Society","publication_identifier":{"issn":["2470-0045"]},"article_processing_charge":"No","month":"10","department":[{"_id":"GaTk"}],"date_updated":"2025-05-05T13:48:04Z","title":"Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons","article_number":"042410","isi":1,"day":"17","volume":98,"oa_version":"Preprint","ec_funded":1,"project":[{"_id":"26436750-B435-11E9-9278-68D0E5697425","name":"Human Brain Project Specific Grant Agreement 2","call_identifier":"H2020","grant_number":"785907"}],"quality_controlled":"1","external_id":{"isi":["000447486100004"]},"main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/content/10.1101/243816v2.full"}],"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."}],"article_type":"original","oa":1,"_id":"31","issue":"4","type":"journal_article","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).","author":[{"first_name":"Ulisse","last_name":"Ferrari","full_name":"Ferrari, Ulisse"},{"full_name":"Deny, Stephane","last_name":"Deny","first_name":"Stephane"},{"full_name":"Chalk, Matthew J","last_name":"Chalk","first_name":"Matthew J"},{"first_name":"Gasper","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik"},{"first_name":"Olivier","last_name":"Marre","full_name":"Marre, Olivier"},{"first_name":"Thierry","full_name":"Mora, Thierry","last_name":"Mora"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","scopus_import":"1","date_created":"2018-12-11T11:44:15Z","language":[{"iso":"eng"}],"publication":"Physical Review E","intvolume":"        98","publist_id":"8024"},{"article_processing_charge":"No","publisher":"Genetics Society of America","doi":"10.1534/genetics.118.300748","publication_status":"published","year":"2018","date_published":"2018-07-01T00:00:00Z","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. <i>Genetics</i>. 2018;209(3):861-883. doi:<a href=\"https://doi.org/10.1534/genetics.118.300748\">10.1534/genetics.118.300748</a>","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.” <i>Genetics</i>. Genetics Society of America, 2018. <a href=\"https://doi.org/10.1534/genetics.118.300748\">https://doi.org/10.1534/genetics.118.300748</a>.","short":"K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, Genetics 209 (2018) 861–883.","apa":"Bodova, K., Priklopil, T., Field, D., Barton, N. H., &#38; Pickup, M. (2018). Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.118.300748\">https://doi.org/10.1534/genetics.118.300748</a>","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,” <i>Genetics</i>, vol. 209, no. 3. Genetics Society of America, pp. 861–883, 2018.","mla":"Bodova, Katarina, et al. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” <i>Genetics</i>, vol. 209, no. 3, Genetics Society of America, 2018, pp. 861–83, doi:<a href=\"https://doi.org/10.1534/genetics.118.300748\">10.1534/genetics.118.300748</a>.","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."},"isi":1,"title":"Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system","date_updated":"2025-04-15T06:50:00Z","department":[{"_id":"NiBa"},{"_id":"GaTk"}],"month":"07","quality_controlled":"1","external_id":{"isi":["000437171700017"]},"project":[{"grant_number":"329960","_id":"25B36484-B435-11E9-9278-68D0E5697425","name":"Mating system and the evolutionary dynamics of hybrid zones","call_identifier":"FP7"},{"grant_number":"250152","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation"},{"grant_number":"291734","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme"}],"ec_funded":1,"oa_version":"Preprint","volume":209,"day":"01","article_type":"original","main_file_link":[{"url":"https://www.biorxiv.org/node/80098.abstract","open_access":"1"}],"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."}],"_id":"316","related_material":{"link":[{"url":"https://ist.ac.at/en/news/recognizing-others-but-not-yourself-new-insights-into-the-evolution-of-plant-mating/","description":"News on IST Homepage","relation":"press_release"}],"record":[{"relation":"research_data","id":"9813","status":"public"}]},"oa":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","author":[{"id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","full_name":"Bodova, Katarina","last_name":"Bodova","orcid":"0000-0002-7214-0171","first_name":"Katarina"},{"first_name":"Tadeas","id":"3C869AA0-F248-11E8-B48F-1D18A9856A87","full_name":"Priklopil, Tadeas","last_name":"Priklopil"},{"orcid":"0000-0002-4014-8478","first_name":"David","last_name":"Field","full_name":"Field, David","id":"419049E2-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Nicholas H","orcid":"0000-0002-8548-5240","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H"},{"orcid":"0000-0001-6118-0541","first_name":"Melinda","last_name":"Pickup","full_name":"Pickup, Melinda","id":"2C78037E-F248-11E8-B48F-1D18A9856A87"}],"type":"journal_article","issue":"3","publication":"Genetics","language":[{"iso":"eng"}],"status":"public","scopus_import":"1","date_created":"2018-12-11T11:45:47Z","page":"861-883","intvolume":"       209"},{"citation":{"mla":"Palmer, Adam, et al. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” <i>Molecular Biology and Evolution</i>, vol. 35, no. 11, Oxford University Press, 2018, pp. 2669–84, doi:<a href=\"https://doi.org/10.1093/molbev/msy163\">10.1093/molbev/msy163</a>.","ieee":"A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates latent potential for antibiotic resistance,” <i>Molecular Biology and Evolution</i>, 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.","chicago":"Palmer, Adam, Remy P Chait, and Roy Kishony. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” <i>Molecular Biology and Evolution</i>. Oxford University Press, 2018. <a href=\"https://doi.org/10.1093/molbev/msy163\">https://doi.org/10.1093/molbev/msy163</a>.","ama":"Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential for antibiotic resistance. <i>Molecular Biology and Evolution</i>. 2018;35(11):2669-2684. doi:<a href=\"https://doi.org/10.1093/molbev/msy163\">10.1093/molbev/msy163</a>","apa":"Palmer, A., Chait, R. P., &#38; Kishony, R. (2018). Nonoptimal gene expression creates latent potential for antibiotic resistance. <i>Molecular Biology and Evolution</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/molbev/msy163\">https://doi.org/10.1093/molbev/msy163</a>","short":"A. Palmer, R.P. Chait, R. Kishony, Molecular Biology and Evolution 35 (2018) 2669–2684."},"year":"2018","date_published":"2018-08-28T00:00:00Z","publication_status":"published","doi":"10.1093/molbev/msy163","publication_identifier":{"issn":["0737-4038"]},"article_processing_charge":"No","publisher":"Oxford University Press","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"month":"08","date_updated":"2023-10-17T11:51:06Z","title":"Nonoptimal gene expression creates latent potential for antibiotic resistance","isi":1,"day":"28","volume":35,"oa_version":"Submitted Version","quality_controlled":"1","external_id":{"pmid":["30169679"],"isi":["000452567200006"]},"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."}],"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pubmed/30169679"}],"article_type":"original","oa":1,"_id":"19","issue":"11","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Adam","last_name":"Palmer","full_name":"Palmer, Adam"},{"first_name":"Remy P","orcid":"0000-0003-0876-3187","full_name":"Chait, Remy P","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","last_name":"Chait"},{"first_name":"Roy","full_name":"Kishony, Roy","last_name":"Kishony"}],"date_created":"2018-12-11T11:44:11Z","status":"public","scopus_import":"1","language":[{"iso":"eng"}],"publication":"Molecular Biology and Evolution","intvolume":"        35","page":"2669 - 2684","pmid":1,"publist_id":"8036"},{"intvolume":"         9","publist_id":"7760","file":[{"date_created":"2018-12-17T16:44:28Z","checksum":"3ba7ab27b27723c7dcf633e8fc1f8f18","access_level":"open_access","relation":"main_file","file_size":1043205,"date_updated":"2020-07-14T12:45:06Z","file_name":"2018_NatureComm_DeMartino.pdf","content_type":"application/pdf","file_id":"5728","creator":"dernst"}],"ddc":["570"],"has_accepted_license":"1","language":[{"iso":"eng"}],"publication":"Nature Communications","status":"public","scopus_import":"1","date_created":"2018-12-11T11:44:57Z","type":"journal_article","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","author":[{"orcid":"0000-0002-5214-4706","first_name":"Daniele","last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","full_name":"De Martino, Daniele"},{"last_name":"Mc","full_name":"Mc, Andersson Anna","first_name":"Andersson Anna"},{"orcid":"0000-0001-5396-4346","first_name":"Tobias","last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","full_name":"Bergmiller, Tobias"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C","last_name":"Guet","first_name":"Calin C","orcid":"0000-0001-6220-2052"},{"orcid":"0000-0002-6699-1455","first_name":"Gasper","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik"}],"file_date_updated":"2020-07-14T12:45:06Z","issue":"1","_id":"161","related_material":{"record":[{"relation":"popular_science","id":"5587","status":"public"}]},"oa":1,"abstract":[{"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.","lang":"eng"}],"project":[{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation"},{"_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734"}],"external_id":{"isi":["000440149300021"]},"quality_controlled":"1","oa_version":"Published Version","day":"30","volume":9,"ec_funded":1,"title":"Statistical mechanics for metabolic networks during steady state growth","isi":1,"article_number":"2988","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"month":"07","department":[{"_id":"GaTk"},{"_id":"CaGu"}],"date_updated":"2025-04-15T06:50:08Z","publication_status":"published","doi":"10.1038/s41467-018-05417-9","article_processing_charge":"No","publisher":"Springer Nature","citation":{"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.” <i>Nature Communications</i>, vol. 9, no. 1, 2988, Springer Nature, 2018, doi:<a href=\"https://doi.org/10.1038/s41467-018-05417-9\">10.1038/s41467-018-05417-9</a>.","ieee":"D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical mechanics for metabolic networks during steady state growth,” <i>Nature Communications</i>, vol. 9, no. 1. Springer Nature, 2018.","apa":"De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., &#38; Tkačik, G. (2018). Statistical mechanics for metabolic networks during steady state growth. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-018-05417-9\">https://doi.org/10.1038/s41467-018-05417-9</a>","short":"D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications 9 (2018).","chicago":"De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet, and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” <i>Nature Communications</i>. Springer Nature, 2018. <a href=\"https://doi.org/10.1038/s41467-018-05417-9\">https://doi.org/10.1038/s41467-018-05417-9</a>.","ama":"De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics for metabolic networks during steady state growth. <i>Nature Communications</i>. 2018;9(1). doi:<a href=\"https://doi.org/10.1038/s41467-018-05417-9\">10.1038/s41467-018-05417-9</a>"},"date_published":"2018-07-30T00:00:00Z","year":"2018"},{"date_updated":"2025-04-15T07:17:08Z","department":[{"_id":"NiBa"},{"_id":"GaTk"}],"month":"04","title":"Supplemental material for Bodova et al., 2018","author":[{"last_name":"Bod'ová","full_name":"Bod'ová, Katarína","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7214-0171","first_name":"Katarína"},{"first_name":"Tadeas","last_name":"Priklopil","id":"3C869AA0-F248-11E8-B48F-1D18A9856A87","full_name":"Priklopil, Tadeas"},{"id":"419049E2-F248-11E8-B48F-1D18A9856A87","full_name":"Field, David","last_name":"Field","orcid":"0000-0002-4014-8478","first_name":"David"},{"first_name":"Nicholas H","orcid":"0000-0002-8548-5240","last_name":"Barton","full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Melinda","orcid":"0000-0001-6118-0541","last_name":"Pickup","full_name":"Pickup, Melinda","id":"2C78037E-F248-11E8-B48F-1D18A9856A87"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","type":"research_data_reference","date_published":"2018-04-30T00:00:00Z","related_material":{"record":[{"id":"316","status":"public","relation":"used_in_publication"}]},"year":"2018","oa":1,"citation":{"ista":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material for Bodova et al., 2018, Genetics Society of America, <a href=\"https://doi.org/10.25386/genetics.6148304.v1\">10.25386/genetics.6148304.v1</a>.","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.","mla":"Bodova, Katarina, et al. <i>Supplemental Material for Bodova et Al., 2018</i>. Genetics Society of America, 2018, doi:<a href=\"https://doi.org/10.25386/genetics.6148304.v1\">10.25386/genetics.6148304.v1</a>.","short":"K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018).","apa":"Bodova, K., Priklopil, T., Field, D., Barton, N. H., &#38; Pickup, M. (2018). Supplemental material for Bodova et al., 2018. Genetics Society of America. <a href=\"https://doi.org/10.25386/genetics.6148304.v1\">https://doi.org/10.25386/genetics.6148304.v1</a>","ama":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material for Bodova et al., 2018. 2018. doi:<a href=\"https://doi.org/10.25386/genetics.6148304.v1\">10.25386/genetics.6148304.v1</a>","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. <a href=\"https://doi.org/10.25386/genetics.6148304.v1\">https://doi.org/10.25386/genetics.6148304.v1</a>."},"_id":"9813","article_processing_charge":"No","publisher":"Genetics Society of America","doi":"10.25386/genetics.6148304.v1","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."}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.25386/genetics.6148304.v1"}],"day":"30","oa_version":"Published Version","status":"public","date_created":"2021-08-06T13:04:32Z"},{"month":"01","department":[{"_id":"GaTk"}],"date_updated":"2025-05-14T10:55:59Z","isi":1,"title":"Toward a unified theory of efficient, predictive, and sparse coding","citation":{"ama":"Chalk MJ, Marre O, Tkačik G. Toward a unified theory of efficient, predictive, and sparse coding. <i>Proceedings of the National Academy of Sciences of the United States of America</i>. 2018;115(1):186-191. doi:<a href=\"https://doi.org/10.1073/pnas.1711114115\">10.1073/pnas.1711114115</a>","chicago":"Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Toward a Unified Theory of Efficient, Predictive, and Sparse Coding.” <i>Proceedings of the National Academy of Sciences of the United States of America</i>. National Academy of Sciences, 2018. <a href=\"https://doi.org/10.1073/pnas.1711114115\">https://doi.org/10.1073/pnas.1711114115</a>.","short":"M.J. Chalk, O. Marre, G. Tkačik, Proceedings of the National Academy of Sciences of the United States of America 115 (2018) 186–191.","apa":"Chalk, M. J., Marre, O., &#38; Tkačik, G. (2018). Toward a unified theory of efficient, predictive, and sparse coding. <i>Proceedings of the National Academy of Sciences of the United States of America</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1711114115\">https://doi.org/10.1073/pnas.1711114115</a>","ieee":"M. J. Chalk, O. Marre, and G. Tkačik, “Toward a unified theory of efficient, predictive, and sparse coding,” <i>Proceedings of the National Academy of Sciences of the United States of America</i>, vol. 115, no. 1. National Academy of Sciences, pp. 186–191, 2018.","mla":"Chalk, Matthew J., et al. “Toward a Unified Theory of Efficient, Predictive, and Sparse Coding.” <i>Proceedings of the National Academy of Sciences of the United States of America</i>, vol. 115, no. 1, National Academy of Sciences, 2018, pp. 186–91, doi:<a href=\"https://doi.org/10.1073/pnas.1711114115\">10.1073/pnas.1711114115</a>.","ista":"Chalk MJ, Marre O, Tkačik G. 2018. Toward a unified theory of efficient, predictive, and sparse coding. Proceedings of the National Academy of Sciences of the United States of America. 115(1), 186–191."},"year":"2018","date_published":"2018-01-02T00:00:00Z","doi":"10.1073/pnas.1711114115","publisher":"National Academy of Sciences","article_processing_charge":"No","publication_status":"published","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/152660 "}],"abstract":[{"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.","lang":"eng"}],"volume":115,"day":"02","oa_version":"Submitted Version","project":[{"_id":"254D1A94-B435-11E9-9278-68D0E5697425","name":"Sensitivity to higher-order statistics in natural scenes","call_identifier":"FWF","grant_number":"P 25651-N26"}],"quality_controlled":"1","external_id":{"isi":["000419128700049"]},"issue":"1","corr_author":"1","type":"journal_article","author":[{"full_name":"Chalk, Matthew J","id":"2BAAC544-F248-11E8-B48F-1D18A9856A87","last_name":"Chalk","orcid":"0000-0001-7782-4436","first_name":"Matthew J"},{"first_name":"Olivier","last_name":"Marre","full_name":"Marre, Olivier"},{"last_name":"Tkacik","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"_id":"543","publist_id":"7273","intvolume":"       115","page":"186 - 191","date_created":"2018-12-11T11:47:04Z","status":"public","scopus_import":"1","language":[{"iso":"eng"}],"publication":"Proceedings of the National Academy of Sciences of the United States of America"},{"datarep_id":"98","file":[{"access_level":"open_access","file_size":1142543971,"relation":"main_file","date_created":"2018-12-12T13:02:24Z","checksum":"6808748837b9afbbbabc2a356ca2b88a","file_id":"5590","creator":"system","file_name":"IST-2018-98-v1+1_BBalls_area2_tile2_20x20.mat","date_updated":"2020-07-14T12:47:07Z","content_type":"application/octet-stream"},{"date_created":"2018-12-12T13:02:25Z","checksum":"d6d6cd07743038fe3a12352983fcf9dd","access_level":"open_access","file_size":702336,"relation":"main_file","date_updated":"2020-07-14T12:47:07Z","file_name":"IST-2018-98-v1+2_ExperimentStructure.pdf","content_type":"application/pdf","file_id":"5591","creator":"system"},{"relation":"main_file","file_size":432,"access_level":"open_access","checksum":"0c9cfb4dab35bb3dc25a04395600b1c8","date_created":"2018-12-12T13:02:26Z","creator":"system","file_id":"5592","content_type":"application/octet-stream","date_updated":"2020-07-14T12:47:07Z","file_name":"IST-2018-98-v1+3_GoodLocations_area2_20x20.mat"},{"creator":"system","file_id":"5593","date_updated":"2020-07-14T12:47:07Z","file_name":"IST-2018-98-v1+4_README.txt","content_type":"text/plain","access_level":"open_access","file_size":986,"relation":"main_file","date_created":"2018-12-12T13:02:26Z","checksum":"2a83b011012e21e934b4596285b1a183"}],"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. "}],"ddc":["570"],"has_accepted_license":"1","project":[{"_id":"254D1A94-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Sensitivity to higher-order statistics in natural scenes","grant_number":"P 25651-N26"}],"oa_version":"Published Version","day":"29","date_created":"2018-12-12T12:31:39Z","status":"public","keyword":["retina","decoding","regression","neural networks","complex stimulus"],"title":"Nonlinear decoding of a complex movie from the mammalian retina","type":"research_data","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Stephane","last_name":"Deny","full_name":"Deny, Stephane"},{"first_name":"Olivier","last_name":"Marre","full_name":"Marre, Olivier"},{"first_name":"Vicente","last_name":"Botella-Soler","full_name":"Botella-Soler, Vicente"},{"last_name":"Martius","id":"3A276B68-F248-11E8-B48F-1D18A9856A87","full_name":"Martius, Georg S","first_name":"Georg S"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455"}],"file_date_updated":"2020-07-14T12:47:07Z","tmp":{"name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","image":"/images/cc_0.png"},"month":"03","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"date_updated":"2025-04-15T08:18:24Z","_id":"5584","doi":"10.15479/AT:ISTA:98","publisher":"Institute of Science and Technology Austria","article_processing_charge":"No","citation":{"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.","mla":"Deny, Stephane, et al. <i>Nonlinear Decoding of a Complex Movie from the Mammalian Retina</i>. Institute of Science and Technology Austria, 2018, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:98\">10.15479/AT:ISTA:98</a>.","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, <a href=\"https://doi.org/10.15479/AT:ISTA:98\">10.15479/AT:ISTA:98</a>.","ama":"Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. Nonlinear decoding of a complex movie from the mammalian retina. 2018. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:98\">10.15479/AT:ISTA:98</a>","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. <a href=\"https://doi.org/10.15479/AT:ISTA:98\">https://doi.org/10.15479/AT:ISTA:98</a>.","short":"S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkačik, (2018).","apa":"Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., &#38; Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:98\">https://doi.org/10.15479/AT:ISTA:98</a>"},"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"292"}]},"oa":1,"year":"2018","date_published":"2018-03-29T00:00:00Z"},{"doi":"10.15479/AT:ISTA:62","publisher":"Institute of Science and Technology Austria","article_processing_charge":"No","_id":"5587","citation":{"ista":"De Martino D, Tkačik G. 2018. Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:62\">10.15479/AT:ISTA:62</a>.","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.","mla":"De Martino, Daniele, and Gašper Tkačik. <i>Supporting Materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.”</i> Institute of Science and Technology Austria, 2018, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:62\">10.15479/AT:ISTA:62</a>.","short":"D. De Martino, G. Tkačik, (2018).","apa":"De Martino, D., &#38; Tkačik, G. (2018). Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:62\">https://doi.org/10.15479/AT:ISTA:62</a>","ama":"De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:62\">10.15479/AT:ISTA:62</a>","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. <a href=\"https://doi.org/10.15479/AT:ISTA:62\">https://doi.org/10.15479/AT:ISTA:62</a>."},"related_material":{"record":[{"relation":"research_paper","id":"161","status":"public"}]},"year":"2018","oa":1,"date_published":"2018-09-21T00:00:00Z","type":"research_data","author":[{"first_name":"Daniele","orcid":"0000-0002-5214-4706","last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","full_name":"De Martino, Daniele"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","orcid":"0000-0002-6699-1455","first_name":"Gasper"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Supporting materials \"STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH\"","month":"09","department":[{"_id":"GaTk"}],"date_updated":"2025-04-15T06:50:08Z","file_date_updated":"2020-07-14T12:47:08Z","tmp":{"name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","image":"/images/cc_0.png"},"has_accepted_license":"1","project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734"},{"call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27"}],"ec_funded":1,"keyword":["metabolic networks","e.coli core","maximum entropy","monte carlo markov chain sampling","ellipsoidal rounding"],"date_created":"2018-12-12T12:31:41Z","status":"public","day":"21","oa_version":"Published Version","datarep_id":"111","ddc":["530"],"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)."}],"file":[{"relation":"main_file","file_size":14376,"access_level":"open_access","checksum":"97992e3e8cf8544ec985a48971708726","date_created":"2018-12-12T13:05:13Z","file_id":"5641","creator":"system","content_type":"application/zip","date_updated":"2020-07-14T12:47:08Z","file_name":"IST-2018-111-v1+1_CODES.zip"}]},{"type":"journal_article","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","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","author":[{"last_name":"Bodova","full_name":"Bodova, Katarina","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7214-0171","first_name":"Katarina"},{"last_name":"Haskovec","full_name":"Haskovec, Jan","first_name":"Jan"},{"first_name":"Peter","full_name":"Markowich, Peter","last_name":"Markowich"}],"corr_author":"1","_id":"607","arxiv":1,"oa":1,"page":"108-120","publist_id":"7198","language":[{"iso":"eng"}],"publication":"Physica D: Nonlinear Phenomena","scopus_import":"1","status":"public","date_created":"2018-12-11T11:47:28Z","title":"Well posedness and maximum entropy approximation for the dynamics of quantitative traits","isi":1,"month":"08","department":[{"_id":"NiBa"},{"_id":"GaTk"}],"date_updated":"2024-10-09T20:58:45Z","publication_status":"published","doi":"10.1016/j.physd.2017.10.015","publisher":"Elsevier","article_processing_charge":"No","citation":{"ama":"Bodova K, Haskovec J, Markowich P. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. <i>Physica D: Nonlinear Phenomena</i>. 2018;376-377:108-120. doi:<a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">10.1016/j.physd.2017.10.015</a>","chicago":"Bodova, Katarina, Jan Haskovec, and Peter Markowich. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” <i>Physica D: Nonlinear Phenomena</i>. Elsevier, 2018. <a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">https://doi.org/10.1016/j.physd.2017.10.015</a>.","short":"K. Bodova, J. Haskovec, P. Markowich, Physica D: Nonlinear Phenomena 376–377 (2018) 108–120.","apa":"Bodova, K., Haskovec, J., &#38; Markowich, P. (2018). Well posedness and maximum entropy approximation for the dynamics of quantitative traits. <i>Physica D: Nonlinear Phenomena</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">https://doi.org/10.1016/j.physd.2017.10.015</a>","ieee":"K. Bodova, J. Haskovec, and P. Markowich, “Well posedness and maximum entropy approximation for the dynamics of quantitative traits,” <i>Physica D: Nonlinear Phenomena</i>, vol. 376–377. Elsevier, pp. 108–120, 2018.","mla":"Bodova, Katarina, et al. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” <i>Physica D: Nonlinear Phenomena</i>, vol. 376–377, Elsevier, 2018, pp. 108–20, doi:<a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">10.1016/j.physd.2017.10.015</a>.","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."},"date_published":"2018-08-01T00:00:00Z","year":"2018","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."}],"main_file_link":[{"url":"https://arxiv.org/abs/1704.08757","open_access":"1"}],"external_id":{"isi":["000437962900012"],"arxiv":["1704.08757"]},"quality_controlled":"1","day":"01","oa_version":"Submitted Version","volume":"376-377"},{"_id":"9831","doi":"10.1371/journal.pone.0193049.s001","article_processing_charge":"No","publisher":"Public Library of Science","citation":{"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. <a href=\"https://doi.org/10.1371/journal.pone.0193049.s001\">https://doi.org/10.1371/journal.pone.0193049.s001</a>.","ama":"Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Implementation of the inference method in Matlab. 2018. doi:<a href=\"https://doi.org/10.1371/journal.pone.0193049.s001\">10.1371/journal.pone.0193049.s001</a>","apa":"Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., &#38; Tkačik, G. (2018). Implementation of the inference method in Matlab. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pone.0193049.s001\">https://doi.org/10.1371/journal.pone.0193049.s001</a>","short":"K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, (2018).","mla":"Bod’Ová, Katarína, et al. <i>Implementation of the Inference Method in Matlab</i>. Public Library of Science, 2018, doi:<a href=\"https://doi.org/10.1371/journal.pone.0193049.s001\">10.1371/journal.pone.0193049.s001</a>.","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, <a href=\"https://doi.org/10.1371/journal.pone.0193049.s001\">10.1371/journal.pone.0193049.s001</a>."},"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"406"}]},"date_published":"2018-03-07T00:00:00Z","year":"2018","title":"Implementation of the inference method in Matlab","type":"research_data_reference","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"last_name":"Bod’Ová","full_name":"Bod’Ová, Katarína","first_name":"Katarína"},{"last_name":"Mitchell","id":"315BCD80-F248-11E8-B48F-1D18A9856A87","full_name":"Mitchell, Gabriel","first_name":"Gabriel"},{"last_name":"Harpaz","full_name":"Harpaz, Roy","first_name":"Roy"},{"first_name":"Elad","last_name":"Schneidman","full_name":"Schneidman, Elad"},{"orcid":"0000-0002-6699-1455","first_name":"Gašper","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper"}],"department":[{"_id":"GaTk"}],"month":"03","date_updated":"2025-04-15T06:44:30Z","oa_version":"Published Version","day":"07","status":"public","date_created":"2021-08-09T07:01:24Z","abstract":[{"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.","lang":"eng"}]},{"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. "}],"volume":13,"day":"07","oa_version":"Submitted Version","pubrep_id":"995","quality_controlled":"1","external_id":{"isi":["000426896800032"]},"project":[{"grant_number":"RGP0065/2012","name":"Information processing and computation in fish groups","_id":"255008E4-B435-11E9-9278-68D0E5697425"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"date_updated":"2025-04-15T06:44:30Z","department":[{"_id":"GaTk"}],"month":"03","title":"Probabilistic models of individual and collective animal behavior","isi":1,"year":"2018","date_published":"2018-03-07T00:00:00Z","citation":{"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).","ieee":"K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkačik, “Probabilistic models of individual and collective animal behavior,” <i>PLoS One</i>, vol. 13, no. 3. Public Library of Science, 2018.","mla":"Bod’Ová, Katarína, et al. “Probabilistic Models of Individual and Collective Animal Behavior.” <i>PLoS One</i>, vol. 13, no. 3, Public Library of Science, 2018, doi:<a href=\"https://doi.org/10.1371/journal.pone.0193049\">10.1371/journal.pone.0193049</a>.","short":"K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, PLoS One 13 (2018).","apa":"Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., &#38; Tkačik, G. (2018). Probabilistic models of individual and collective animal behavior. <i>PLoS One</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pone.0193049\">https://doi.org/10.1371/journal.pone.0193049</a>","ama":"Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Probabilistic models of individual and collective animal behavior. <i>PLoS One</i>. 2018;13(3). doi:<a href=\"https://doi.org/10.1371/journal.pone.0193049\">10.1371/journal.pone.0193049</a>","chicago":"Bod’Ová, Katarína, Gabriel Mitchell, Roy Harpaz, Elad Schneidman, and Gašper Tkačik. “Probabilistic Models of Individual and Collective Animal Behavior.” <i>PLoS One</i>. Public Library of Science, 2018. <a href=\"https://doi.org/10.1371/journal.pone.0193049\">https://doi.org/10.1371/journal.pone.0193049</a>."},"publication_status":"published","article_processing_charge":"Yes","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0193049","file":[{"content_type":"application/pdf","date_updated":"2020-07-14T12:46:22Z","file_name":"IST-2018-995-v1+1_2018_Bodova_Probabilistic.pdf","file_id":"5165","creator":"system","checksum":"684229493db75b43e98a46cd922da497","date_created":"2018-12-12T10:15:43Z","relation":"main_file","file_size":6887358,"access_level":"open_access"}],"ddc":["530","571"],"intvolume":"        13","publist_id":"7423","date_created":"2018-12-11T11:46:18Z","status":"public","scopus_import":"1","has_accepted_license":"1","publication":"PLoS One","language":[{"iso":"eng"}],"file_date_updated":"2020-07-14T12:46:22Z","corr_author":"1","issue":"3","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","acknowledgement":"This work was supported by the Human Frontier Science Program RGP0065/2012 (GT, ES).","author":[{"last_name":"Bod’Ová","full_name":"Bod’Ová, Katarína","first_name":"Katarína"},{"id":"315BCD80-F248-11E8-B48F-1D18A9856A87","full_name":"Mitchell, Gabriel","last_name":"Mitchell","first_name":"Gabriel"},{"full_name":"Harpaz, Roy","last_name":"Harpaz","first_name":"Roy"},{"first_name":"Elad","last_name":"Schneidman","full_name":"Schneidman, Elad"},{"orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper"}],"type":"journal_article","oa":1,"related_material":{"record":[{"relation":"research_data","status":"public","id":"9831"}]},"_id":"406"},{"month":"06","department":[{"_id":"GaTk"}],"date_updated":"2026-04-08T13:55:45Z","isi":1,"title":"Distributed and dynamic intracellular organization of extracellular information","citation":{"short":"A. Granados, J. Pietsch, S.A. Cepeda Humerez, I. Farquhar, G. Tkačik, P. Swain, PNAS 115 (2018) 6088–6093.","apa":"Granados, A., Pietsch, J., Cepeda Humerez, S. A., Farquhar, I., Tkačik, G., &#38; Swain, P. (2018). Distributed and dynamic intracellular organization of extracellular information. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1716659115\">https://doi.org/10.1073/pnas.1716659115</a>","ama":"Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. Distributed and dynamic intracellular organization of extracellular information. <i>PNAS</i>. 2018;115(23):6088-6093. doi:<a href=\"https://doi.org/10.1073/pnas.1716659115\">10.1073/pnas.1716659115</a>","chicago":"Granados, Alejandro, Julian Pietsch, Sarah A Cepeda Humerez, Isebail Farquhar, Gašper Tkačik, and Peter Swain. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” <i>PNAS</i>. National Academy of Sciences, 2018. <a href=\"https://doi.org/10.1073/pnas.1716659115\">https://doi.org/10.1073/pnas.1716659115</a>.","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.","ieee":"A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkačik, and P. Swain, “Distributed and dynamic intracellular organization of extracellular information,” <i>PNAS</i>, vol. 115, no. 23. National Academy of Sciences, pp. 6088–6093, 2018.","mla":"Granados, Alejandro, et al. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” <i>PNAS</i>, vol. 115, no. 23, National Academy of Sciences, 2018, pp. 6088–93, doi:<a href=\"https://doi.org/10.1073/pnas.1716659115\">10.1073/pnas.1716659115</a>."},"year":"2018","date_published":"2018-06-05T00:00:00Z","doi":"10.1073/pnas.1716659115","publisher":"National Academy of Sciences","article_processing_charge":"No","publication_status":"published","article_type":"original","main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/content/early/2017/09/21/192039"}],"abstract":[{"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.","lang":"eng"}],"day":"05","oa_version":"Preprint","volume":115,"project":[{"grant_number":"P28844-B27","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation"}],"quality_controlled":"1","external_id":{"pmid":["29784812"],"isi":["000434114900071"]},"issue":"23","type":"journal_article","author":[{"first_name":"Alejandro","full_name":"Granados, Alejandro","last_name":"Granados"},{"last_name":"Pietsch","full_name":"Pietsch, Julian","first_name":"Julian"},{"first_name":"Sarah A","last_name":"Cepeda Humerez","full_name":"Cepeda Humerez, Sarah A","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Farquhar","full_name":"Farquhar, Isebail","first_name":"Isebail"},{"last_name":"Tkacik","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper","orcid":"0000-0002-6699-1455"},{"full_name":"Swain, Peter","last_name":"Swain","first_name":"Peter"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","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.).","related_material":{"record":[{"relation":"part_of_dissertation","id":"6473","status":"public"}]},"oa":1,"_id":"281","publist_id":"7618","pmid":1,"page":"6088 - 6093","intvolume":"       115","date_created":"2018-12-11T11:45:35Z","scopus_import":"1","status":"public","language":[{"iso":"eng"}],"publication":"PNAS"},{"ec_funded":1,"volume":2,"oa_version":"None","day":"01","external_id":{"isi":["000426516400027"]},"quality_controlled":"1","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"},{"grant_number":"RGY0079/2011","name":"Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems","_id":"251BCBEC-B435-11E9-9278-68D0E5697425"},{"_id":"251D65D8-B435-11E9-9278-68D0E5697425","name":"Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level","grant_number":"24210"}],"abstract":[{"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","lang":"eng"}],"date_published":"2018-02-01T00:00:00Z","year":"2018","citation":{"short":"M. Pleska, M. Lang, D. Refardt, B. Levin, C.C. Guet, Nature Ecology and Evolution 2 (2018) 359–366.","apa":"Pleska, M., Lang, M., Refardt, D., Levin, B., &#38; Guet, C. C. (2018). Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. <i>Nature Ecology and Evolution</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41559-017-0424-z\">https://doi.org/10.1038/s41559-017-0424-z</a>","ama":"Pleska M, Lang M, Refardt D, Levin B, Guet CC. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. <i>Nature Ecology and Evolution</i>. 2018;2(2):359-366. doi:<a href=\"https://doi.org/10.1038/s41559-017-0424-z\">10.1038/s41559-017-0424-z</a>","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.” <i>Nature Ecology and Evolution</i>. Springer Nature, 2018. <a href=\"https://doi.org/10.1038/s41559-017-0424-z\">https://doi.org/10.1038/s41559-017-0424-z</a>.","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.","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,” <i>Nature Ecology and Evolution</i>, vol. 2, no. 2. Springer Nature, pp. 359–366, 2018.","mla":"Pleska, Maros, et al. “Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with Innate Immunity.” <i>Nature Ecology and Evolution</i>, vol. 2, no. 2, Springer Nature, 2018, pp. 359–66, doi:<a href=\"https://doi.org/10.1038/s41559-017-0424-z\">10.1038/s41559-017-0424-z</a>."},"publisher":"Springer Nature","article_processing_charge":"No","doi":"10.1038/s41559-017-0424-z","publication_status":"published","date_updated":"2026-04-08T14:19:43Z","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"month":"02","isi":1,"title":"Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity","date_created":"2018-12-11T11:46:35Z","status":"public","scopus_import":"1","publication":"Nature Ecology and Evolution","language":[{"iso":"eng"}],"publist_id":"7364","page":"359 - 366","intvolume":"         2","related_material":{"record":[{"relation":"dissertation_contains","id":"202","status":"public"}]},"_id":"457","corr_author":"1","issue":"2","author":[{"orcid":"0000-0001-7460-7479","first_name":"Maros","last_name":"Pleska","full_name":"Pleska, Maros","id":"4569785E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Moritz","full_name":"Lang, Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","last_name":"Lang"},{"first_name":"Dominik","last_name":"Refardt","full_name":"Refardt, Dominik"},{"full_name":"Levin, Bruce","last_name":"Levin","first_name":"Bruce"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C","last_name":"Guet","orcid":"0000-0001-6220-2052","first_name":"Calin C"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","type":"journal_article"}]