[{"author":[{"first_name":"Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","last_name":"Lang","full_name":"Lang, Moritz"},{"first_name":"Eduardo","last_name":"Sontag","full_name":"Sontag, Eduardo"}],"conference":{"location":"Boston, MA, USA","start_date":"2016-07-06","end_date":"2016-07-08","name":"ACC: American Control Conference"},"date_published":"2016-07-28T00:00:00Z","quality_controlled":"1","OA_type":"green","article_processing_charge":"No","date_created":"2018-12-11T11:51:21Z","_id":"1320","acknowledgement":"The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement n° [291734]. Work supported in part by grants AFOSR FA9550-14-1-0060 and NIH 1R01GM100473.","publisher":"IEEE","doi":"10.1109/ACC.2016.7526722","type":"conference","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","file":[{"checksum":"7219432b43defc62a0d45f48d4ce6a19","relation":"main_file","date_updated":"2025-06-25T11:46:36Z","access_level":"open_access","creator":"system","file_size":539166,"file_id":"5203","content_type":"application/pdf","file_name":"IST-2017-810-v1+1_root.pdf","date_created":"2018-12-12T10:16:17Z"}],"title":"Scale-invariant systems realize nonlinear differential operators","project":[{"name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"year":"2016","abstract":[{"lang":"eng","text":"In recent years, several biomolecular systems have been shown to be scale-invariant (SI), i.e. to show the same output dynamics when exposed to geometrically scaled input signals (u → pu, p > 0) after pre-adaptation to accordingly scaled constant inputs. In this article, we show that SI systems-as well as systems invariant with respect to other input transformations-can realize nonlinear differential operators: when excited by inputs obeying functional forms characteristic for a given class of invariant systems, the systems' outputs converge to constant values directly quantifying the speed of the input."}],"date_updated":"2025-06-25T11:46:37Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","pubrep_id":"810","day":"28","file_date_updated":"2025-06-25T11:46:36Z","language":[{"iso":"eng"}],"month":"07","has_accepted_license":"1","publist_id":"5950","oa_version":"Submitted Version","oa":1,"OA_place":"repository","scopus_import":"1","article_number":"7526722","status":"public","ddc":["003","621"],"citation":{"ama":"Lang M, Sontag E. Scale-invariant systems realize nonlinear differential operators. In: Vol 2016-July. IEEE; 2016. doi:10.1109/ACC.2016.7526722","mla":"Lang, Moritz, and Eduardo Sontag. Scale-Invariant Systems Realize Nonlinear Differential Operators. Vol. 2016–July, 7526722, IEEE, 2016, doi:10.1109/ACC.2016.7526722.","chicago":"Lang, Moritz, and Eduardo Sontag. “Scale-Invariant Systems Realize Nonlinear Differential Operators,” Vol. 2016–July. IEEE, 2016. https://doi.org/10.1109/ACC.2016.7526722.","ista":"Lang M, Sontag E. 2016. Scale-invariant systems realize nonlinear differential operators. ACC: American Control Conference vol. 2016–July, 7526722.","apa":"Lang, M., & Sontag, E. (2016). Scale-invariant systems realize nonlinear differential operators (Vol. 2016–July). Presented at the ACC: American Control Conference, Boston, MA, USA: IEEE. https://doi.org/10.1109/ACC.2016.7526722","ieee":"M. Lang and E. Sontag, “Scale-invariant systems realize nonlinear differential operators,” presented at the ACC: American Control Conference, Boston, MA, USA, 2016, vol. 2016–July.","short":"M. Lang, E. Sontag, in:, IEEE, 2016."},"volume":"2016-July","ec_funded":1},{"article_number":"10333","status":"public","scopus_import":"1","has_accepted_license":"1","oa_version":"Published Version","publist_id":"5936","oa":1,"volume":7,"citation":{"ista":"Chait RP, Palmer A, Yelin I, Kishony R. 2016. Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. 7, 10333.","short":"R.P. Chait, A. Palmer, I. Yelin, R. Kishony, Nature Communications 7 (2016).","apa":"Chait, R. P., Palmer, A., Yelin, I., & Kishony, R. (2016). Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms10333","ieee":"R. P. Chait, A. Palmer, I. Yelin, and R. Kishony, “Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments,” Nature Communications, vol. 7. Nature Publishing Group, 2016.","ama":"Chait RP, Palmer A, Yelin I, Kishony R. Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. 2016;7. doi:10.1038/ncomms10333","mla":"Chait, Remy P., et al. “Pervasive Selection for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.” Nature Communications, vol. 7, 10333, Nature Publishing Group, 2016, doi:10.1038/ncomms10333.","chicago":"Chait, Remy P, Adam Palmer, Idan Yelin, and Roy Kishony. “Pervasive Selection for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms10333."},"ddc":["570","579"],"date_updated":"2025-09-22T08:22:19Z","publication":"Nature Communications","abstract":[{"lang":"eng","text":"Antibiotic-sensitive and -resistant bacteria coexist in natural environments with low, if detectable, antibiotic concentrations. Except possibly around localized antibiotic sources, where resistance can provide a strong advantage, bacterial fitness is dominated by stresses unaffected by resistance to the antibiotic. How do such mixed and heterogeneous conditions influence the selective advantage or disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels of tetracyclines potentiate selection for or against tetracycline resistance around localized sources of almost any toxin or stress. Furthermore, certain stresses generate alternating rings of selection for and against resistance around a localized source of the antibiotic. In these conditions, localized antibiotic sources, even at high strengths, can actually produce a net selection against resistance to the antibiotic. Our results show that interactions between the effects of an antibiotic and other stresses in inhomogeneous environments can generate pervasive, complex patterns of selection both for and against antibiotic resistance."}],"isi":1,"year":"2016","month":"01","language":[{"iso":"eng"}],"pubrep_id":"662","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","file_date_updated":"2020-07-14T12:44:44Z","day":"20","publication_status":"published","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"Nature Publishing Group","type":"journal_article","doi":"10.1038/ncomms10333","title":"Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments","file":[{"access_level":"open_access","creator":"system","file_size":1844107,"file_id":"5039","content_type":"application/pdf","file_name":"IST-2016-662-v1+1_ncomms10333.pdf","date_created":"2018-12-12T10:13:52Z","checksum":"ef147bcbb8bd37e9079cf3ce06f5815d","relation":"main_file","date_updated":"2020-07-14T12:44:44Z"}],"quality_controlled":"1","external_id":{"isi":["000369021700002"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"date_published":"2016-01-20T00:00:00Z","author":[{"full_name":"Chait, Remy P","first_name":"Remy P","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-0876-3187","last_name":"Chait"},{"first_name":"Adam","last_name":"Palmer","full_name":"Palmer, Adam"},{"first_name":"Idan","last_name":"Yelin","full_name":"Yelin, Idan"},{"first_name":"Roy","last_name":"Kishony","full_name":"Kishony, Roy"}],"intvolume":" 7","acknowledgement":"This work was partially supported by US National Institutes of Health grant R01-GM081617, Israeli Centers of Research Excellence I-CORE Program ISF Grant No. 152/11, and the European Research Council FP7 ERC Grant 281891.","_id":"1332","article_processing_charge":"No","date_created":"2018-12-11T11:51:25Z"},{"date_published":"2016-09-09T00:00:00Z","external_id":{"isi":["000382626800052"]},"quality_controlled":"1","intvolume":" 353","author":[{"full_name":"Baym, Michael","first_name":"Michael","last_name":"Baym"},{"first_name":"Tami","last_name":"Lieberman","full_name":"Lieberman, Tami"},{"first_name":"Eric","last_name":"Kelsic","full_name":"Kelsic, Eric"},{"last_name":"Chait","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-0876-3187","first_name":"Remy P","full_name":"Chait, Remy P"},{"full_name":"Gross, Rotem","first_name":"Rotem","last_name":"Gross"},{"last_name":"Yelin","first_name":"Idan","full_name":"Yelin, Idan"},{"full_name":"Kishony, Roy","last_name":"Kishony","first_name":"Roy"}],"_id":"1342","page":"1147 - 1151","date_created":"2018-12-11T11:51:29Z","article_processing_charge":"No","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","doi":"10.1126/science.aag0822","type":"journal_article","publisher":"American Association for the Advancement of Science","title":"Spatiotemporal microbial evolution on antibiotic landscapes","issue":"6304","publication":"Science","date_updated":"2025-09-22T08:17:11Z","year":"2016","isi":1,"abstract":[{"text":"A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front.While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front,we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behindmore sensitive lineages.TheMEGA-plate provides a versatile platformfor studying microbial adaption and directly visualizing evolutionary dynamics.","lang":"eng"}],"month":"09","day":"09","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}],"scopus_import":"1","status":"public","oa":1,"oa_version":"Preprint","publist_id":"5911","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5534434/","open_access":"1"}],"citation":{"chicago":"Baym, Michael, Tami Lieberman, Eric Kelsic, Remy P Chait, Rotem Gross, Idan Yelin, and Roy Kishony. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.” Science. American Association for the Advancement of Science, 2016. https://doi.org/10.1126/science.aag0822.","ama":"Baym M, Lieberman T, Kelsic E, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016;353(6304):1147-1151. doi:10.1126/science.aag0822","mla":"Baym, Michael, et al. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.” Science, vol. 353, no. 6304, American Association for the Advancement of Science, 2016, pp. 1147–51, doi:10.1126/science.aag0822.","ieee":"M. Baym et al., “Spatiotemporal microbial evolution on antibiotic landscapes,” Science, vol. 353, no. 6304. American Association for the Advancement of Science, pp. 1147–1151, 2016.","apa":"Baym, M., Lieberman, T., Kelsic, E., Chait, R. P., Gross, R., Yelin, I., & Kishony, R. (2016). Spatiotemporal microbial evolution on antibiotic landscapes. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aag0822","short":"M. Baym, T. Lieberman, E. Kelsic, R.P. Chait, R. Gross, I. Yelin, R. Kishony, Science 353 (2016) 1147–1151.","ista":"Baym M, Lieberman T, Kelsic E, Chait RP, Gross R, Yelin I, Kishony R. 2016. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 353(6304), 1147–1151."},"volume":353},{"author":[{"last_name":"Friedlander","id":"36A5845C-F248-11E8-B48F-1D18A9856A87","first_name":"Tamar","full_name":"Friedlander, Tamar"},{"full_name":"Prizak, Roshan","first_name":"Roshan","id":"4456104E-F248-11E8-B48F-1D18A9856A87","last_name":"Prizak"},{"first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","last_name":"Guet","full_name":"Guet, Calin C"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","last_name":"Barton"},{"last_name":"Tkacik","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper"}],"intvolume":" 7","external_id":{"isi":["000380858400001"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"date_published":"2016-08-04T00:00:00Z","quality_controlled":"1","corr_author":"1","article_processing_charge":"No","date_created":"2018-12-11T11:51:34Z","related_material":{"record":[{"id":"6071","status":"public","relation":"dissertation_contains"}]},"_id":"1358","publisher":"Nature Publishing Group","type":"journal_article","doi":"10.1038/ncomms12307","department":[{"_id":"GaTk"},{"_id":"NiBa"},{"_id":"CaGu"}],"publication_status":"published","file":[{"date_updated":"2020-07-14T12:44:46Z","relation":"main_file","checksum":"fe3f3a1526d180b29fe691ab11435b78","date_created":"2018-12-12T10:12:01Z","file_name":"IST-2016-627-v1+1_ncomms12307.pdf","content_type":"application/pdf","file_id":"4919","creator":"system","file_size":861805,"access_level":"open_access"},{"date_updated":"2020-07-14T12:44:46Z","checksum":"164864a1a675f3ad80e9917c27aba07f","relation":"main_file","date_created":"2018-12-12T10:12:02Z","content_type":"application/pdf","file_name":"IST-2016-627-v1+2_ncomms12307-s1.pdf","file_id":"4920","access_level":"open_access","creator":"system","file_size":1084703}],"project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"},{"name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152"},{"name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"}],"title":"Intrinsic limits to gene regulation by global crosstalk","isi":1,"year":"2016","abstract":[{"text":"Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements.","lang":"eng"}],"publication":"Nature Communications","date_updated":"2026-04-08T13:54:24Z","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","pubrep_id":"627","day":"04","file_date_updated":"2020-07-14T12:44:46Z","language":[{"iso":"eng"}],"month":"08","oa":1,"oa_version":"Published Version","publist_id":"5887","has_accepted_license":"1","scopus_import":"1","article_number":"12307","status":"public","ddc":["576"],"citation":{"mla":"Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications, vol. 7, 12307, Nature Publishing Group, 2016, doi:10.1038/ncomms12307.","ama":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307","chicago":"Friedlander, Tamar, Roshan Prizak, Calin C Guet, Nicholas H Barton, and Gašper Tkačik. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms12307.","ista":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 7, 12307.","short":"T. Friedlander, R. Prizak, C.C. Guet, N.H. Barton, G. Tkačik, Nature Communications 7 (2016).","apa":"Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms12307","ieee":"T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic limits to gene regulation by global crosstalk,” Nature Communications, vol. 7. Nature Publishing Group, 2016."},"volume":7,"ec_funded":1},{"doi":"10.1088/1478-3975/13/3/036005","type":"journal_article","publisher":"IOP Publishing","publication_status":"published","department":[{"_id":"GaTk"}],"issue":"3","project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"title":"Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli","intvolume":" 13","author":[{"first_name":"Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","last_name":"De Martino","full_name":"De Martino, Daniele"},{"first_name":"Fabrizio","last_name":"Capuani","full_name":"Capuani, Fabrizio"},{"first_name":"Andrea","last_name":"De Martino","full_name":"De Martino, Andrea"}],"quality_controlled":"1","date_published":"2016-05-27T00:00:00Z","external_id":{"isi":["000380148200014"],"arxiv":["1601.03243"]},"date_created":"2018-12-11T11:51:46Z","article_processing_charge":"No","acknowledgement":"The research leading to these results has received funding from the from the Marie\r\nCurie Action ITN NETADIS, grant agreement no. 290038.","_id":"1394","main_file_link":[{"url":"https://arxiv.org/abs/1601.03243","open_access":"1"}],"arxiv":1,"oa":1,"publist_id":"5815","oa_version":"Preprint","status":"public","article_number":"036005","scopus_import":"1","ec_funded":1,"volume":13,"citation":{"chicago":"De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology. IOP Publishing, 2016. https://doi.org/10.1088/1478-3975/13/3/036005.","ama":"De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005","mla":"De Martino, Daniele, et al. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology, vol. 13, no. 3, 036005, IOP Publishing, 2016, doi:10.1088/1478-3975/13/3/036005.","ieee":"D. De Martino, F. Capuani, and A. De Martino, “Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli,” Physical Biology, vol. 13, no. 3. IOP Publishing, 2016.","apa":"De Martino, D., Capuani, F., & De Martino, A. (2016). Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. IOP Publishing. https://doi.org/10.1088/1478-3975/13/3/036005","short":"D. De Martino, F. Capuani, A. De Martino, Physical Biology 13 (2016).","ista":"De Martino D, Capuani F, De Martino A. 2016. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 13(3), 036005."},"abstract":[{"text":"The solution space of genome-scale models of cellular metabolism provides a map between physically\r\nviable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the\r\ncorresponding growth rates. By sampling the solution space of E. coliʼs metabolic network, we show\r\nthat empirical growth rate distributions recently obtained in experiments at single-cell resolution can\r\nbe explained in terms of a trade-off between the higher fitness of fast-growing phenotypes and the\r\nhigher entropy of slow-growing ones. Based on this, we propose a minimal model for the evolution of\r\na large bacterial population that captures this trade-off. The scaling relationships observed in\r\nexperiments encode, in such frameworks, for the same distance from the maximum achievable growth\r\nrate, the same degree of growth rate maximization, and/or the same rate of phenotypic change. Being\r\ngrounded on genome-scale metabolic network reconstructions, these results allow for multiple\r\nimplications and extensions in spite of the underlying conceptual simplicity.","lang":"eng"}],"year":"2016","isi":1,"date_updated":"2025-09-18T14:31:33Z","publication":"Physical Biology","language":[{"iso":"eng"}],"day":"27","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","month":"05"},{"department":[{"_id":"GaTk"},{"_id":"NiBa"}],"publication_status":"published","doi":"10.1534/genetics.115.184127","type":"journal_article","publisher":"Genetics Society of America","title":"A general approximation for the dynamics of quantitative traits","project":[{"name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"grant_number":"RGP0065/2012","_id":"255008E4-B435-11E9-9278-68D0E5697425","name":"Information processing and computation in fish groups"}],"issue":"4","date_published":"2016-04-06T00:00:00Z","external_id":{"isi":["000373959100022"],"arxiv":["1510.08344"]},"quality_controlled":"1","intvolume":" 202","author":[{"full_name":"Bod'ová, Katarína","orcid":"0000-0002-7214-0171","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","first_name":"Katarína","last_name":"Bod'ová"},{"last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","full_name":"Tkacik, Gasper"},{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H","last_name":"Barton","full_name":"Barton, Nicholas H"}],"_id":"1420","page":"1523 - 1548","date_created":"2018-12-11T11:51:55Z","corr_author":"1","article_processing_charge":"No","scopus_import":"1","status":"public","oa":1,"publist_id":"5787","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1510.08344"}],"arxiv":1,"citation":{"chicago":"Bodova, Katarina, Gašper Tkačik, and Nicholas H Barton. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.184127.","ama":"Bodova K, Tkačik G, Barton NH. A general approximation for the dynamics of quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127","mla":"Bodova, Katarina, et al. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics, vol. 202, no. 4, Genetics Society of America, 2016, pp. 1523–48, doi:10.1534/genetics.115.184127.","short":"K. Bodova, G. Tkačik, N.H. Barton, Genetics 202 (2016) 1523–1548.","ieee":"K. Bodova, G. Tkačik, and N. H. Barton, “A general approximation for the dynamics of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of America, pp. 1523–1548, 2016.","apa":"Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation for the dynamics of quantitative traits. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.184127","ista":"Bodova K, Tkačik G, Barton NH. 2016. A general approximation for the dynamics of quantitative traits. Genetics. 202(4), 1523–1548."},"ec_funded":1,"volume":202,"publication":"Genetics","date_updated":"2025-09-18T14:22:05Z","year":"2016","isi":1,"abstract":[{"text":"Selection, mutation, and random drift affect the dynamics of allele frequencies and consequently of quantitative traits. While the macroscopic dynamics of quantitative traits can be measured, the underlying allele frequencies are typically unobserved. Can we understand how the macroscopic observables evolve without following these microscopic processes? This problem has been studied previously by analogy with statistical mechanics: the allele frequency distribution at each time point is approximated by the stationary form, which maximizes entropy. We explore the limitations of this method when mutation is small (4Nμ < 1) so that populations are typically close to fixation, and we extend the theory in this regime to account for changes in mutation strength. We consider a single diallelic locus either under directional selection or with overdominance and then generalize to multiple unlinked biallelic loci with unequal effects. We find that the maximum-entropy approximation is remarkably accurate, even when mutation and selection change rapidly. ","lang":"eng"}],"month":"04","day":"06","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}]},{"ec_funded":1,"volume":13,"citation":{"ista":"De Martino D. 2016. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 13(1), 016003.","short":"D. De Martino, Physical Biology 13 (2016).","apa":"De Martino, D. (2016). Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. IOP Publishing. https://doi.org/10.1088/1478-3975/13/1/016003","ieee":"D. De Martino, “Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis,” Physical Biology, vol. 13, no. 1. IOP Publishing, 2016.","mla":"De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology, vol. 13, no. 1, 016003, IOP Publishing, 2016, doi:10.1088/1478-3975/13/1/016003.","ama":"De Martino D. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 2016;13(1). doi:10.1088/1478-3975/13/1/016003","chicago":"De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology. IOP Publishing, 2016. https://doi.org/10.1088/1478-3975/13/1/016003."},"status":"public","article_number":"016003","scopus_import":"1","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1505.04613"}],"arxiv":1,"oa_version":"Preprint","oa":1,"publist_id":"5702","month":"01","language":[{"iso":"eng"}],"day":"29","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","date_updated":"2025-09-18T11:34:17Z","publication":"Physical Biology","abstract":[{"lang":"eng","text":"In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism."}],"year":"2016","isi":1,"title":"Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis","project":[{"name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"issue":"1","publication_status":"published","department":[{"_id":"GaTk"}],"type":"journal_article","doi":"10.1088/1478-3975/13/1/016003","publisher":"IOP Publishing","_id":"1485","date_created":"2018-12-11T11:52:18Z","corr_author":"1","article_processing_charge":"No","quality_controlled":"1","date_published":"2016-01-29T00:00:00Z","external_id":{"arxiv":["1505.04613"],"isi":["000371585200003"]},"intvolume":" 13","author":[{"orcid":"0000-0002-5214-4706","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","first_name":"Daniele","last_name":"De Martino","full_name":"De Martino, Daniele"}]},{"has_accepted_license":"1","oa_version":"Published Version","oa":1,"publication_identifier":{"isbn":["9780262339360"]},"scopus_import":"1","status":"public","ddc":["610"],"citation":{"mla":"Martius, Georg S., et al. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.” 15th International Conference on the Synthesis and Simulation of Living Systems, vol. 28, MIT Press, 2016, pp. 142–43, doi:10.7551/978-0-262-33936-0-ch029.","ama":"Martius GS, Hostettler R, Knoll A, Der R. Self-organized control of an tendon driven arm by differential extrinsic plasticity. In: 15th International Conference on the Synthesis and Simulation of Living Systems. Vol 28. MIT Press; 2016:142-143. doi:10.7551/978-0-262-33936-0-ch029","chicago":"Martius, Georg S, Rafael Hostettler, Alois Knoll, and Ralf Der. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.” In 15th International Conference on the Synthesis and Simulation of Living Systems, 28:142–43. MIT Press, 2016. https://doi.org/10.7551/978-0-262-33936-0-ch029.","ista":"Martius GS, Hostettler R, Knoll A, Der R. 2016. Self-organized control of an tendon driven arm by differential extrinsic plasticity. 15th International Conference on the Synthesis and Simulation of Living Systems. ALIFE 2016: Conference on the Synthesis and Simulation of Living Systems vol. 28, 142–143.","ieee":"G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Self-organized control of an tendon driven arm by differential extrinsic plasticity,” in 15th International Conference on the Synthesis and Simulation of Living Systems, Cancun, Mexico, 2016, vol. 28, pp. 142–143.","apa":"Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Self-organized control of an tendon driven arm by differential extrinsic plasticity. In 15th International Conference on the Synthesis and Simulation of Living Systems (Vol. 28, pp. 142–143). Cancun, Mexico: MIT Press. https://doi.org/10.7551/978-0-262-33936-0-ch029","short":"G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, 15th International Conference on the Synthesis and Simulation of Living Systems, MIT Press, 2016, pp. 142–143."},"volume":28,"ec_funded":1,"year":"2016","abstract":[{"lang":"eng","text":"With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. The idea is that the controller controls the world---the body plus its environment---as reliably as possible. This paper focuses on new lines of self-organization for developmental robotics. We apply the recently developed differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object's internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently discovers how to rotate it. In this way, the robot discovers affordances of objects its body is interacting with."}],"publication":"15th International Conference on the Synthesis and Simulation of Living Systems","date_updated":"2025-07-10T11:55:05Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2020-07-14T12:48:09Z","day":"01","language":[{"iso":"eng"}],"month":"09","publisher":"MIT Press","doi":"10.7551/978-0-262-33936-0-ch029","type":"conference","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"publication_status":"published","file":[{"file_name":"2016_ProcALIFE_Martius.pdf","content_type":"application/pdf","date_created":"2020-07-06T12:59:09Z","creator":"cziletti","file_size":678670,"access_level":"open_access","file_id":"8096","relation":"main_file","checksum":"cff63e7a4b8ac466ba51a9c84153a940","date_updated":"2020-07-14T12:48:09Z"}],"title":"Self-organized control of an tendon driven arm by differential extrinsic plasticity","project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"author":[{"first_name":"Georg S","id":"3A276B68-F248-11E8-B48F-1D18A9856A87","last_name":"Martius","full_name":"Martius, Georg S"},{"last_name":"Hostettler","first_name":"Rafael","full_name":"Hostettler, Rafael"},{"full_name":"Knoll, Alois","first_name":"Alois","last_name":"Knoll"},{"full_name":"Der, Ralf","first_name":"Ralf","last_name":"Der"}],"intvolume":" 28","conference":{"name":"ALIFE 2016: Conference on the Synthesis and Simulation of Living Systems","start_date":"2016-07-04","location":"Cancun, Mexico","end_date":"2016-07-08"},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"date_published":"2016-09-01T00:00:00Z","quality_controlled":"1","page":"142-143","corr_author":"1","article_processing_charge":"No","date_created":"2020-07-05T22:00:47Z","_id":"8094"},{"date_updated":"2025-06-03T11:18:32Z","abstract":[{"text":"Experience constantly shapes neural circuits through a variety of plasticity mechanisms. While the functional roles of some plasticity mechanisms are well-understood, it remains unclear how changes in neural excitability contribute to learning. Here, we develop a normative interpretation of intrinsic plasticity (IP) as a key component of unsupervised learning. We introduce a novel generative mixture model that accounts for the class-specific statistics of stimulus intensities, and we derive a neural circuit that learns the input classes and their intensities. We will analytically show that inference and learning for our generative model can be achieved by a neural circuit with intensity-sensitive neurons equipped with a specific form of IP. Numerical experiments verify our analytical derivations and show robust behavior for artificial and natural stimuli. Our results link IP to non-trivial input statistics, in particular the statistics of stimulus intensities for classes to which a neuron is sensitive. More generally, our work paves the way toward new classification algorithms that are robust to intensity variations.","lang":"eng"}],"year":"2016","month":"01","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","alternative_title":["Advances in Neural Information Processing Systems"],"day":"01","status":"public","scopus_import":"1","main_file_link":[{"open_access":"1","url":"https://papers.nips.cc/paper/6582-neurons-equipped-with-intrinsic-plasticity-learn-stimulus-intensity-statistics"}],"oa":1,"oa_version":"None","publist_id":"6469","volume":29,"ec_funded":1,"citation":{"chicago":"Monk, Travis, Cristina Savin, and Jörg Lücke. “Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics,” 29:4285–93. Neural Information Processing Systems Foundation, 2016.","mla":"Monk, Travis, et al. Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics. Vol. 29, Neural Information Processing Systems Foundation, 2016, pp. 4285–93.","ama":"Monk T, Savin C, Lücke J. Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. In: Vol 29. Neural Information Processing Systems Foundation; 2016:4285-4293.","short":"T. Monk, C. Savin, J. Lücke, in:, Neural Information Processing Systems Foundation, 2016, pp. 4285–4293.","apa":"Monk, T., Savin, C., & Lücke, J. (2016). Neurons equipped with intrinsic plasticity learn stimulus intensity statistics (Vol. 29, pp. 4285–4293). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine: Neural Information Processing Systems Foundation.","ieee":"T. Monk, C. Savin, and J. Lücke, “Neurons equipped with intrinsic plasticity learn stimulus intensity statistics,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine, 2016, vol. 29, pp. 4285–4293.","ista":"Monk T, Savin C, Lücke J. 2016. Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 4285–4293."},"quality_controlled":"1","conference":{"end_date":"2016-12-10","start_date":"2016-12-05","location":"Barcelona, Spaine","name":"NIPS: Neural Information Processing Systems"},"date_published":"2016-01-01T00:00:00Z","author":[{"first_name":"Travis","last_name":"Monk","full_name":"Monk, Travis"},{"id":"3933349E-F248-11E8-B48F-1D18A9856A87","first_name":"Cristina","last_name":"Savin","full_name":"Savin, Cristina"},{"last_name":"Lücke","first_name":"Jörg","full_name":"Lücke, Jörg"}],"intvolume":" 29","acknowledgement":"DFG Cluster of Excellence EXC 1077/1 (Hearing4all) and LU 1196/5-1 (JL and TM), People Programme (Marie Curie Actions) FP7/2007-2013 grant agreement no. 291734 (CS)","_id":"948","article_processing_charge":"No","date_created":"2018-12-11T11:49:21Z","page":"4285 - 4293","publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Neural Information Processing Systems Foundation","type":"conference","title":"Neurons equipped with intrinsic plasticity learn stimulus intensity statistics","project":[{"call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme"}]},{"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","day":"27","article_processing_charge":"No","related_material":{"record":[{"id":"1270","status":"public","relation":"used_in_publication"}]},"date_created":"2021-08-10T08:53:48Z","_id":"9869","month":"09","year":"2016","abstract":[{"lang":"eng","text":"A lower bound on the error of a positional estimator with limited positional information is derived."}],"author":[{"full_name":"Hillenbrand, Patrick","first_name":"Patrick","last_name":"Hillenbrand"},{"first_name":"Ulrich","last_name":"Gerland","full_name":"Gerland, Ulrich"},{"first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","full_name":"Tkačik, Gašper"}],"date_published":"2016-09-27T00:00:00Z","date_updated":"2025-09-22T08:46:14Z","citation":{"ama":"Hillenbrand P, Gerland U, Tkačik G. Error bound on an estimator of position. 2016. doi:10.1371/journal.pone.0163628.s001","mla":"Hillenbrand, Patrick, et al. Error Bound on an Estimator of Position. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s001.","chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Error Bound on an Estimator of Position.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s001.","ista":"Hillenbrand P, Gerland U, Tkačik G. 2016. Error bound on an estimator of position, Public Library of Science, 10.1371/journal.pone.0163628.s001.","apa":"Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Error bound on an estimator of position. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s001","ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Error bound on an estimator of position.” Public Library of Science, 2016.","short":"P. Hillenbrand, U. Gerland, G. Tkačik, (2016)."},"title":"Error bound on an estimator of position","publisher":"Public Library of Science","oa_version":"Published Version","doi":"10.1371/journal.pone.0163628.s001","type":"research_data_reference","department":[{"_id":"GaTk"}],"status":"public"},{"_id":"9870","month":"09","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","day":"27","article_processing_charge":"No","related_material":{"record":[{"id":"1270","status":"public","relation":"used_in_publication"}]},"date_created":"2021-08-10T09:23:45Z","date_published":"2016-09-27T00:00:00Z","date_updated":"2025-09-22T08:46:14Z","year":"2016","author":[{"last_name":"Hillenbrand","first_name":"Patrick","full_name":"Hillenbrand, Patrick"},{"first_name":"Ulrich","last_name":"Gerland","full_name":"Gerland, Ulrich"},{"last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper","full_name":"Tkačik, Gašper"}],"abstract":[{"lang":"eng","text":"The effect of noise in the input field on an Ising model is approximated. Furthermore, methods to compute positional information in an Ising model by transfer matrices and Monte Carlo sampling are outlined."}],"title":"Computation of positional information in an Ising model","citation":{"ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information in an Ising model.” Public Library of Science, 2016.","apa":"Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in an Ising model. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s002","short":"P. Hillenbrand, U. Gerland, G. Tkačik, (2016).","ista":"Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information in an Ising model, Public Library of Science, 10.1371/journal.pone.0163628.s002.","chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of Positional Information in an Ising Model.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s002.","ama":"Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in an Ising model. 2016. doi:10.1371/journal.pone.0163628.s002","mla":"Hillenbrand, Patrick, et al. Computation of Positional Information in an Ising Model. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s002."},"department":[{"_id":"GaTk"}],"status":"public","publisher":"Public Library of Science","oa_version":"Published Version","type":"research_data_reference","doi":"10.1371/journal.pone.0163628.s002"},{"_id":"9871","month":"09","article_processing_charge":"No","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"1270"}]},"date_created":"2021-08-10T09:27:35Z","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","day":"27","date_updated":"2025-09-22T08:46:14Z","abstract":[{"lang":"eng","text":"The positional information in a discrete morphogen field with Gaussian noise is computed."}],"author":[{"first_name":"Patrick","last_name":"Hillenbrand","full_name":"Hillenbrand, Patrick"},{"full_name":"Gerland, Ulrich","first_name":"Ulrich","last_name":"Gerland"},{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","last_name":"Tkačik","full_name":"Tkačik, Gašper"}],"year":"2016","citation":{"chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of Positional Information in a Discrete Morphogen Field.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s003.","ama":"Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in a discrete morphogen field. 2016. doi:10.1371/journal.pone.0163628.s003","mla":"Hillenbrand, Patrick, et al. Computation of Positional Information in a Discrete Morphogen Field. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s003.","ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information in a discrete morphogen field.” Public Library of Science, 2016.","apa":"Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in a discrete morphogen field. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s003","short":"P. Hillenbrand, U. Gerland, G. Tkačik, (2016).","ista":"Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information in a discrete morphogen field, Public Library of Science, 10.1371/journal.pone.0163628.s003."},"title":"Computation of positional information in a discrete morphogen field","status":"public","department":[{"_id":"GaTk"}],"publisher":"Public Library of Science","oa_version":"Published Version","type":"research_data_reference","doi":"10.1371/journal.pone.0163628.s003"},{"external_id":{"isi":["000391853100010"]},"date_published":"2016-11-15T00:00:00Z","quality_controlled":"1","OA_type":"green","author":[{"id":"29E0800A-F248-11E8-B48F-1D18A9856A87","first_name":"Moritz","last_name":"Lang","full_name":"Lang, Moritz"},{"full_name":"Stelling, Jörg","first_name":"Jörg","last_name":"Stelling"}],"intvolume":" 38","_id":"1170","page":"B988 - B1008","article_processing_charge":"No","corr_author":"1","date_created":"2018-12-11T11:50:31Z","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","publisher":"Society for Industrial and Applied Mathematics","type":"journal_article","doi":"10.1137/15M103306X","title":"Modular parameter identification of biomolecular networks","file":[{"date_updated":"2025-06-25T11:26:45Z","checksum":"781bc3ffd30b2dd65b7727c5a285fc78","relation":"main_file","date_created":"2018-12-12T10:14:41Z","content_type":"application/pdf","file_name":"IST-2017-811-v1+1_modular_parameter_identification.pdf","file_id":"5095","access_level":"open_access","file_size":871964,"creator":"system"}],"issue":"6","publication":"SIAM Journal on Scientific Computing","das_tickbox":"1","date_updated":"2026-07-06T14:00:20Z","isi":1,"year":"2016","abstract":[{"text":"The increasing complexity of dynamic models in systems and synthetic biology poses computational challenges especially for the identification of model parameters. While modularization of the corresponding optimization problems could help reduce the “curse of dimensionality,” abundant feedback and crosstalk mechanisms prohibit a simple decomposition of most biomolecular networks into subnetworks, or modules. Drawing on ideas from network modularization and multiple-shooting optimization, we present here a modular parameter identification approach that explicitly allows for such interdependencies. Interfaces between our modules are given by the experimentally measured molecular species. This definition allows deriving good (initial) estimates for the inter-module communication directly from the experimental data. Given these estimates, the states and parameter sensitivities of different modules can be integrated independently. To achieve consistency between modules, we iteratively adjust the estimates for inter-module communication while optimizing the parameters. After convergence to an optimal parameter set---but not during earlier iterations---the intermodule communication as well as the individual modules\\' state dynamics agree with the dynamics of the nonmodularized network. Our modular parameter identification approach allows for easy parallelization; it can reduce the computational complexity for larger networks and decrease the probability to converge to suboptimal local minima. We demonstrate the algorithm\\'s performance in parameter estimation for two biomolecular networks, a synthetic genetic oscillator and a mammalian signaling pathway.","lang":"eng"}],"month":"11","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","pubrep_id":"811","file_date_updated":"2025-06-25T11:26:45Z","day":"15","language":[{"iso":"eng"}],"article_type":"original","scopus_import":"1","status":"public","oa_version":"Submitted Version","has_accepted_license":"1","oa":1,"publist_id":"6186","OA_place":"repository","citation":{"ama":"Lang M, Stelling J. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 2016;38(6):B988-B1008. doi:10.1137/15M103306X","mla":"Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular Networks.” SIAM Journal on Scientific Computing, vol. 38, no. 6, Society for Industrial and Applied Mathematics, 2016, pp. B988–1008, doi:10.1137/15M103306X.","chicago":"Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular Networks.” SIAM Journal on Scientific Computing. Society for Industrial and Applied Mathematics, 2016. https://doi.org/10.1137/15M103306X.","ista":"Lang M, Stelling J. 2016. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 38(6), B988–B1008.","short":"M. Lang, J. Stelling, SIAM Journal on Scientific Computing 38 (2016) B988–B1008.","ieee":"M. Lang and J. Stelling, “Modular parameter identification of biomolecular networks,” SIAM Journal on Scientific Computing, vol. 38, no. 6. Society for Industrial and Applied Mathematics, pp. B988–B1008, 2016.","apa":"Lang, M., & Stelling, J. (2016). Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/15M103306X"},"volume":38,"ddc":["003","518","570","621"]},{"citation":{"mla":"De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism &amp; Growth.” Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 12, 123502, IOP Publishing, 2016, doi:10.1088/1742-5468/aa4e8f.","ama":"De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth. Journal of Statistical Mechanics: Theory and Experiment. 2016;2016(12). doi:10.1088/1742-5468/aa4e8f","chicago":"De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism &amp; Growth.” Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing, 2016. https://doi.org/10.1088/1742-5468/aa4e8f.","ista":"De Martino D, Masoero D. 2016. Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth. Journal of Statistical Mechanics: Theory and Experiment. 2016(12), 123502.","short":"D. De Martino, D. Masoero, Journal of Statistical Mechanics: Theory and Experiment 2016 (2016).","apa":"De Martino, D., & Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth. Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing. https://doi.org/10.1088/1742-5468/aa4e8f","ieee":"D. De Martino and D. Masoero, “Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 12. IOP Publishing, 2016."},"ec_funded":1,"volume":2016,"publist_id":"6165","oa":1,"oa_version":"Preprint","main_file_link":[{"url":"https://arxiv.org/abs/1606.09048","open_access":"1"}],"arxiv":1,"scopus_import":"1","status":"public","article_number":"123502","day":"30","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"month":"12","year":"2016","isi":1,"abstract":[{"lang":"eng","text":"We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. \r\nIn the asymptotic regime of slow\r\ndiffusion, that coincides with the relevant experimental range, the resulting\r\nnon-linear Fokker–Planck equation is solved for the steady state in the WKB\r\napproximation that maps it into the ground state of a quantum particle in an\r\nAiry potential plus a centrifugal term. We retrieve scaling laws for growth rate\r\nfluctuations and time response with respect to the distance from the maximum\r\ngrowth rate suggesting that suboptimal populations can have a faster response\r\nto perturbations."}],"publication":"Journal of Statistical Mechanics: Theory and Experiment","date_updated":"2026-07-07T13:11:22Z","das_tickbox":"1","issue":"12","project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"title":"Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth","doi":"10.1088/1742-5468/aa4e8f","type":"journal_article","publisher":"IOP Publishing","department":[{"_id":"GaTk"}],"publication_status":"published","date_created":"2018-12-11T11:50:37Z","article_processing_charge":"No","_id":"1188","acknowledgement":"D De Martino is supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. D Masoero is supported by the FCT scholarship, number SFRH/BPD/75908/2011. D De Martino thanks the Grupo de Física Matemática of the Universidade de Lisboa for the kind hospitality. We also wish to thank Matteo Osella, Vincenzo Vitagliano and Vera Luz Masoero for useful discussions, also late at night.","intvolume":" 2016","author":[{"full_name":"De Martino, Daniele","last_name":"De Martino","first_name":"Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706"},{"last_name":"Masoero","first_name":"Davide","full_name":"Masoero, Davide"}],"date_published":"2016-12-30T00:00:00Z","external_id":{"isi":["000391973900001"],"arxiv":["1606.09048"]},"quality_controlled":"1"},{"date_published":"2016-08-01T00:00:00Z","author":[{"last_name":"Rieckh","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","full_name":"Rieckh, Georg"}],"_id":"1128","page":"114","date_created":"2018-12-11T11:50:18Z","article_processing_charge":"No","corr_author":"1","department":[{"_id":"GaTk"},{"_id":"GradSch"}],"publication_status":"published","type":"dissertation","publisher":"Institute of Science and Technology Austria","title":"Studying the complexities of transcriptional regulation","file":[{"date_updated":"2019-08-13T11:46:25Z","relation":"main_file","checksum":"ec453918c3bf8e6f460fd1156ef7b493","file_id":"6815","file_size":2614660,"creator":"dernst","access_level":"closed","date_created":"2019-08-13T11:46:25Z","file_name":"Thesis_Georg_Rieckh_w_signature_page.pdf","content_type":"application/pdf"},{"checksum":"51ae398166370d18fd22478b6365c4da","relation":"main_file","date_updated":"2020-09-21T11:30:40Z","success":1,"access_level":"open_access","file_size":6096178,"creator":"dernst","file_id":"8542","content_type":"application/pdf","file_name":"Thesis_Georg_Rieckh.pdf","date_created":"2020-09-21T11:30:40Z"}],"supervisor":[{"first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","full_name":"Tkacik, Gasper"}],"date_updated":"2026-07-29T11:29:22Z","year":"2016","abstract":[{"text":"The process of gene expression is central to the modern understanding of how cellular systems\r\nfunction. In this process, a special kind of regulatory proteins, called transcription factors,\r\nare important to determine how much protein is produced from a given gene. As biological\r\ninformation is transmitted from transcription factor concentration to mRNA levels to amounts of\r\nprotein, various sources of noise arise and pose limits to the fidelity of intracellular signaling.\r\nThis thesis concerns itself with several aspects of stochastic gene expression: (i) the mathematical\r\ndescription of complex promoters responsible for the stochastic production of biomolecules,\r\n(ii) fundamental limits to information processing the cell faces due to the interference from multiple\r\nfluctuating signals, (iii) how the presence of gene expression noise influences the evolution\r\nof regulatory sequences, (iv) and tools for the experimental study of origins and consequences\r\nof cell-cell heterogeneity, including an application to bacterial stress response systems.","lang":"eng"}],"month":"08","file_date_updated":"2020-09-21T11:30:40Z","day":"01","alternative_title":["ISTA Thesis"],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","language":[{"iso":"eng"}],"publication_identifier":{"issn":["2663-337X"]},"status":"public","publist_id":"6232","has_accepted_license":"1","oa_version":"Published Version","oa":1,"OA_place":"publisher","degree_awarded":"PhD","citation":{"chicago":"Rieckh, Georg. “Studying the Complexities of Transcriptional Regulation.” Institute of Science and Technology Austria, 2016.","ama":"Rieckh G. Studying the complexities of transcriptional regulation. 2016.","mla":"Rieckh, Georg. Studying the Complexities of Transcriptional Regulation. Institute of Science and Technology Austria, 2016.","short":"G. Rieckh, Studying the Complexities of Transcriptional Regulation, Institute of Science and Technology Austria, 2016.","apa":"Rieckh, G. (2016). Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria.","ieee":"G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute of Science and Technology Austria, 2016.","ista":"Rieckh G. 2016. Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria."},"doi_confirm":"1","ddc":["570"]},{"publist_id":"6088","oa_version":"Preprint","oa":1,"arxiv":1,"main_file_link":[{"url":"https://arxiv.org/abs/1507.02562","open_access":"1"}],"scopus_import":"1","article_number":"022404","status":"public","citation":{"ista":"Sokolowski TR, Walczak A, Bialek W, Tkačik G. 2016. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E. 93(2), 022404.","short":"T.R. Sokolowski, A. Walczak, W. Bialek, G. Tkačik, Physical Review E 93 (2016).","apa":"Sokolowski, T. R., Walczak, A., Bialek, W., & Tkačik, G. (2016). Extending the dynamic range of transcription factor action by translational regulation. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.93.022404","ieee":"T. R. Sokolowski, A. Walczak, W. Bialek, and G. Tkačik, “Extending the dynamic range of transcription factor action by translational regulation,” Physical Review E, vol. 93, no. 2. American Physical Society, 2016.","ama":"Sokolowski TR, Walczak A, Bialek W, Tkačik G. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E. 2016;93(2). doi:10.1103/PhysRevE.93.022404","mla":"Sokolowski, Thomas R., et al. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” Physical Review E, vol. 93, no. 2, 022404, American Physical Society, 2016, doi:10.1103/PhysRevE.93.022404.","chicago":"Sokolowski, Thomas R, Aleksandra Walczak, William Bialek, and Gašper Tkačik. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” Physical Review E. American Physical Society, 2016. https://doi.org/10.1103/PhysRevE.93.022404."},"volume":93,"isi":1,"year":"2016","abstract":[{"text":"A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression.","lang":"eng"}],"publication":"Physical Review E","date_updated":"2026-08-12T14:28:33Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"04","language":[{"iso":"eng"}],"month":"02","publisher":"American Physical Society","doi":"10.1103/PhysRevE.93.022404","type":"journal_article","department":[{"_id":"GaTk"}],"publication_status":"published","issue":"2","title":"Extending the dynamic range of transcription factor action by translational regulation","project":[{"name":"Biophysics of information processing in gene regulation","_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","call_identifier":"FWF"}],"author":[{"full_name":"Sokolowski, Thomas R","first_name":"Thomas R","orcid":"0000-0002-1287-3779","id":"3E999752-F248-11E8-B48F-1D18A9856A87","last_name":"Sokolowski"},{"last_name":"Walczak","first_name":"Aleksandra","full_name":"Walczak, Aleksandra"},{"full_name":"Bialek, William","first_name":"William","last_name":"Bialek"},{"first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","full_name":"Tkacik, Gasper"}],"intvolume":" 93","external_id":{"arxiv":["1507.02562"],"isi":["000369439100005"]},"date_published":"2016-02-04T00:00:00Z","quality_controlled":"1","article_processing_charge":"No","date_created":"2018-12-11T11:50:54Z","_id":"1242","acknowledgement":"We thank T. Gregor, A. Prochaintz, and others for\r\nhelpful discussions. This work was supported in part by\r\nGrants No. PHY-1305525 and No. CCF-0939370 from the\r\nUS National Science Foundation and by the W.M. Keck\r\nFoundation. A.M.W. acknowledges the support by European\r\nResearch Council (ERC) Grant No. MCCIG PCIG10–GA-\r\n2011–303561. G.T. and T.R.S. were supported by Austrian\r\nScience Fund (FWF) Grant No. P28844S."},{"language":[{"iso":"eng"}],"day":"30","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","month":"06","abstract":[{"lang":"eng","text":"Systems biology rests on the idea that biological complexity can be better unraveled through the interplay of modeling and experimentation. However, the success of this approach depends critically on the informativeness of the chosen experiments, which is usually unknown a priori. Here, we propose a systematic scheme based on iterations of optimal experiment design, flow cytometry experiments, and Bayesian parameter inference to guide the discovery process in the case of stochastic biochemical reaction networks. To illustrate the benefit of our methodology, we apply it to the characterization of an engineered light-inducible gene expression circuit in yeast and compare the performance of the resulting model with models identified from nonoptimal experiments. In particular, we compare the parameter posterior distributions and the precision to which the outcome of future experiments can be predicted. Moreover, we illustrate how the identified stochastic model can be used to determine light induction patterns that make either the average amount of protein or the variability in a population of cells follow a desired profile. Our results show that optimal experiment design allows one to derive models that are accurate enough to precisely predict and regulate the protein expression in heterogeneous cell populations over extended periods of time."}],"year":"2015","isi":1,"date_updated":"2025-09-23T09:24:24Z","publication":"PNAS","pmid":1,"ec_funded":1,"volume":112,"citation":{"short":"J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, J. Lygeros, PNAS 112 (2015) 8148–8153.","apa":"Ruess, J., Parise, F., Milias Argeitis, A., Khammash, M., & Lygeros, J. (2015). Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1423947112","ieee":"J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, and J. Lygeros, “Iterative experiment design guides the characterization of a light-inducible gene expression circuit,” PNAS, vol. 112, no. 26. National Academy of Sciences, pp. 8148–8153, 2015.","ista":"Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. 2015. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 112(26), 8148–8153.","chicago":"Ruess, Jakob, Francesca Parise, Andreas Milias Argeitis, Mustafa Khammash, and John Lygeros. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1423947112.","mla":"Ruess, Jakob, et al. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS, vol. 112, no. 26, National Academy of Sciences, 2015, pp. 8148–53, doi:10.1073/pnas.1423947112.","ama":"Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 2015;112(26):8148-8153. doi:10.1073/pnas.1423947112"},"main_file_link":[{"url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491780/","open_access":"1"}],"oa":1,"publist_id":"5633","oa_version":"Submitted Version","status":"public","scopus_import":"1","date_created":"2018-12-11T11:52:36Z","article_processing_charge":"No","page":"8148 - 8153","acknowledgement":"J.R., F.P., and J.L. acknowledge support from the European Commission under the Network of Excellence HYCON2 (highly-complex and networked control systems) and SystemsX.ch under the SignalX Project. J.R. acknowledges support from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013 under REA (Research Executive Agency) Grant 291734. M.K. acknowledges support from Human Frontier Science Program Grant RP0061/2011 (www.hfsp.org). ","_id":"1538","intvolume":" 112","author":[{"orcid":"0000-0003-1615-3282","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","first_name":"Jakob","last_name":"Ruess","full_name":"Ruess, Jakob"},{"full_name":"Parise, Francesca","last_name":"Parise","first_name":"Francesca"},{"last_name":"Milias Argeitis","first_name":"Andreas","full_name":"Milias Argeitis, Andreas"},{"first_name":"Mustafa","last_name":"Khammash","full_name":"Khammash, Mustafa"},{"full_name":"Lygeros, John","first_name":"John","last_name":"Lygeros"}],"quality_controlled":"1","date_published":"2015-06-30T00:00:00Z","external_id":{"pmid":["26085136"],"isi":["000357079400070"]},"issue":"26","title":"Iterative experiment design guides the characterization of a light-inducible gene expression circuit","project":[{"call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme"}],"type":"journal_article","doi":"10.1073/pnas.1423947112","publisher":"National Academy of Sciences","publication_status":"published","department":[{"_id":"ToHe"},{"_id":"GaTk"}]},{"intvolume":" 143","author":[{"full_name":"Ruess, Jakob","first_name":"Jakob","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1615-3282","last_name":"Ruess"}],"quality_controlled":"1","date_published":"2015-12-22T00:00:00Z","external_id":{"isi":["000370412900068"]},"date_created":"2018-12-11T11:52:36Z","article_processing_charge":"No","corr_author":"1","_id":"1539","doi":"10.1063/1.4937937","type":"journal_article","publisher":"American Institute of Physics","publication_status":"published","department":[{"_id":"ToHe"},{"_id":"GaTk"}],"issue":"24","file":[{"date_updated":"2020-07-14T12:45:01Z","relation":"main_file","checksum":"838657118ae286463a2b7737319f35ce","date_created":"2018-12-12T10:07:43Z","file_name":"IST-2016-593-v1+1_Minimal_moment_equations.pdf","content_type":"application/pdf","file_id":"4641","creator":"system","file_size":605355,"access_level":"open_access"}],"title":"Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space","project":[{"name":"Quantitative Reactive Modeling","call_identifier":"FP7","grant_number":"267989","_id":"25EE3708-B435-11E9-9278-68D0E5697425"},{"name":"Rigorous Systems Engineering","call_identifier":"FWF","_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23"},{"grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Formal methods for the design and analysis of complex systems"},{"name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"abstract":[{"text":"Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space. ","lang":"eng"}],"year":"2015","isi":1,"date_updated":"2025-09-23T09:34:48Z","publication":"Journal of Chemical Physics","language":[{"iso":"eng"}],"day":"22","file_date_updated":"2020-07-14T12:45:01Z","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","pubrep_id":"593","month":"12","oa_version":"Published Version","has_accepted_license":"1","oa":1,"publist_id":"5632","status":"public","article_number":"244103","scopus_import":"1","ddc":["000"],"ec_funded":1,"volume":143,"citation":{"short":"J. Ruess, Journal of Chemical Physics 143 (2015).","apa":"Ruess, J. (2015). Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. American Institute of Physics. https://doi.org/10.1063/1.4937937","ieee":"J. Ruess, “Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space,” Journal of Chemical Physics, vol. 143, no. 24. American Institute of Physics, 2015.","ista":"Ruess J. 2015. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 143(24), 244103.","chicago":"Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics. American Institute of Physics, 2015. https://doi.org/10.1063/1.4937937.","ama":"Ruess J. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 2015;143(24). doi:10.1063/1.4937937","mla":"Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics, vol. 143, no. 24, 244103, American Institute of Physics, 2015, doi:10.1063/1.4937937."}},{"volume":9,"ec_funded":1,"citation":{"chicago":"Gilson, Matthieu, Cristina Savin, and Friedemann Zenke. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience. Frontiers Research Foundation, 2015. https://doi.org/10.3389/fncom.2015.00145.","ama":"Gilson M, Savin C, Zenke F. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 2015;9(11). doi:10.3389/fncom.2015.00145","mla":"Gilson, Matthieu, et al. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience, vol. 9, no. 11, 145, Frontiers Research Foundation, 2015, doi:10.3389/fncom.2015.00145.","ieee":"M. Gilson, C. Savin, and F. Zenke, “Editorial: Emergent neural computation from the interaction of different forms of plasticity,” Frontiers in Computational Neuroscience, vol. 9, no. 11. Frontiers Research Foundation, 2015.","apa":"Gilson, M., Savin, C., & Zenke, F. (2015). Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2015.00145","short":"M. Gilson, C. Savin, F. Zenke, Frontiers in Computational Neuroscience 9 (2015).","ista":"Gilson M, Savin C, Zenke F. 2015. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 9(11), 145."},"ddc":["570"],"article_number":"145","status":"public","scopus_import":"1","oa_version":"Published Version","oa":1,"has_accepted_license":"1","publist_id":"5607","month":"11","language":[{"iso":"eng"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","pubrep_id":"479","day":"30","file_date_updated":"2020-07-14T12:45:02Z","date_updated":"2025-09-23T08:35:56Z","publication":"Frontiers in Computational Neuroscience","isi":1,"year":"2015","project":[{"call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme"}],"title":"Editorial: Emergent neural computation from the interaction of different forms of plasticity","issue":"11","file":[{"checksum":"cea73b6d3ef1579f32da10b82f4de4fd","relation":"main_file","date_updated":"2020-07-14T12:45:02Z","access_level":"open_access","creator":"system","file_size":187038,"file_id":"4927","content_type":"application/pdf","file_name":"IST-2016-479-v1+1_fncom-09-00145.pdf","date_created":"2018-12-12T10:12:09Z"}],"publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Frontiers Research Foundation","type":"journal_article","doi":"10.3389/fncom.2015.00145","_id":"1564","article_processing_charge":"No","corr_author":"1","date_created":"2018-12-11T11:52:45Z","quality_controlled":"1","external_id":{"isi":["000365824800002"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"date_published":"2015-11-30T00:00:00Z","author":[{"first_name":"Matthieu","last_name":"Gilson","full_name":"Gilson, Matthieu"},{"full_name":"Savin, Cristina","id":"3933349E-F248-11E8-B48F-1D18A9856A87","first_name":"Cristina","last_name":"Savin"},{"last_name":"Zenke","first_name":"Friedemann","full_name":"Zenke, Friedemann"}],"intvolume":" 9"},{"_id":"1570","page":"E6224 - E6232","date_created":"2018-12-11T11:52:47Z","article_processing_charge":"No","corr_author":"1","date_published":"2015-11-10T00:00:00Z","external_id":{"isi":["000364470300020"],"pmid":["26504200"]},"quality_controlled":"1","intvolume":" 112","author":[{"full_name":"Der, Ralf","last_name":"Der","first_name":"Ralf"},{"full_name":"Martius, Georg S","last_name":"Martius","first_name":"Georg S","id":"3A276B68-F248-11E8-B48F-1D18A9856A87"}],"title":"Novel plasticity rule can explain the development of sensorimotor intelligence","project":[{"call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme"}],"issue":"45","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"publication_status":"published","type":"journal_article","doi":"10.1073/pnas.1508400112","publisher":"National Academy of Sciences","month":"11","day":"10","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}],"publication":"PNAS","date_updated":"2025-09-23T09:41:37Z","year":"2015","isi":1,"abstract":[{"lang":"eng","text":"Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher-level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no systemspecific modifications of the DEP rule. They rather arise from the underlying mechanism of spontaneous symmetry breaking,which is due to the tight brain body environment coupling. The new synaptic rule is biologically plausible and would be an interesting target for neurobiological investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution."}],"citation":{"short":"R. Der, G.S. Martius, PNAS 112 (2015) E6224–E6232.","apa":"Der, R., & Martius, G. S. (2015). Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1508400112","ieee":"R. Der and G. S. Martius, “Novel plasticity rule can explain the development of sensorimotor intelligence,” PNAS, vol. 112, no. 45. National Academy of Sciences, pp. E6224–E6232, 2015.","ista":"Der R, Martius GS. 2015. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 112(45), E6224–E6232.","chicago":"Der, Ralf, and Georg S Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1508400112.","mla":"Der, Ralf, and Georg S. Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.” PNAS, vol. 112, no. 45, National Academy of Sciences, 2015, pp. E6224–32, doi:10.1073/pnas.1508400112.","ama":"Der R, Martius GS. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 2015;112(45):E6224-E6232. doi:10.1073/pnas.1508400112"},"ec_funded":1,"volume":112,"pmid":1,"scopus_import":"1","status":"public","publist_id":"5601","oa":1,"oa_version":"Submitted Version","main_file_link":[{"open_access":"1","url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653169/"}]}]