[{"issue":"3","file_date_updated":"2020-07-14T12:46:22Z","scopus_import":"1","isi":1,"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).","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>","short":"K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, PLoS One 13 (2018).","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.","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>","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>.","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>."},"intvolume":"        13","has_accepted_license":"1","status":"public","acknowledgement":"This work was supported by the Human Frontier Science Program RGP0065/2012 (GT, ES).","title":"Probabilistic models of individual and collective animal behavior","_id":"406","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","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. "}],"day":"07","publist_id":"7423","publication_status":"published","date_created":"2018-12-11T11:46:18Z","author":[{"last_name":"Bod’Ová","full_name":"Bod’Ová, Katarína","first_name":"Katarína"},{"last_name":"Mitchell","full_name":"Mitchell, Gabriel","first_name":"Gabriel","id":"315BCD80-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Harpaz","full_name":"Harpaz, Roy","first_name":"Roy"},{"full_name":"Schneidman, Elad","first_name":"Elad","last_name":"Schneidman"},{"first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik","orcid":"0000-0002-6699-1455"}],"pubrep_id":"995","department":[{"_id":"GaTk"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"related_material":{"record":[{"relation":"research_data","status":"public","id":"9831"}]},"year":"2018","language":[{"iso":"eng"}],"ddc":["530","571"],"oa_version":"Submitted Version","external_id":{"isi":["000426896800032"]},"type":"journal_article","date_published":"2018-03-07T00:00:00Z","project":[{"name":"Information processing and computation in fish groups","_id":"255008E4-B435-11E9-9278-68D0E5697425","grant_number":"RGP0065/2012"}],"volume":13,"file":[{"access_level":"open_access","file_name":"IST-2018-995-v1+1_2018_Bodova_Probabilistic.pdf","checksum":"684229493db75b43e98a46cd922da497","date_updated":"2020-07-14T12:46:22Z","file_size":6887358,"content_type":"application/pdf","file_id":"5165","date_created":"2018-12-12T10:15:43Z","relation":"main_file","creator":"system"}],"quality_controlled":"1","oa":1,"month":"03","doi":"10.1371/journal.pone.0193049","date_updated":"2023-09-15T12:06:19Z","publisher":"Public Library of Science","publication":"PLoS One","article_processing_charge":"Yes"},{"page":"359 - 366","author":[{"last_name":"Pleska","orcid":"0000-0001-7460-7479","id":"4569785E-F248-11E8-B48F-1D18A9856A87","first_name":"Maros","full_name":"Pleska, Maros"},{"last_name":"Lang","full_name":"Lang, Moritz","first_name":"Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Dominik","full_name":"Refardt, Dominik","last_name":"Refardt"},{"first_name":"Bruce","full_name":"Levin, Bruce","last_name":"Levin"},{"last_name":"Guet","orcid":"0000-0001-6220-2052","first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C"}],"publication_status":"published","publist_id":"7364","day":"01","date_created":"2018-12-11T11:46:35Z","year":"2018","language":[{"iso":"eng"}],"related_material":{"record":[{"id":"202","status":"public","relation":"dissertation_contains"}]},"department":[{"_id":"CaGu"},{"_id":"GaTk"}],"volume":2,"project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"},{"grant_number":"RGY0079/2011","_id":"251BCBEC-B435-11E9-9278-68D0E5697425","name":"Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems (HFSP Young investigators' grant)"},{"name":"Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level (DOC Fellowship)","_id":"251D65D8-B435-11E9-9278-68D0E5697425","grant_number":"24210"}],"date_published":"2018-02-01T00:00:00Z","type":"journal_article","oa_version":"None","external_id":{"isi":["000426516400027"]},"publication":"Nature Ecology and Evolution","doi":"10.1038/s41559-017-0424-z","publisher":"Springer Nature","date_updated":"2023-09-15T12:04:57Z","article_processing_charge":"No","quality_controlled":"1","month":"02","issue":"2","isi":1,"scopus_import":"1","ec_funded":1,"status":"public","citation":{"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.","short":"M. Pleska, M. Lang, D. Refardt, B. Levin, C.C. Guet, Nature Ecology and Evolution 2 (2018) 359–366.","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.","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>","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>.","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>","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>."},"intvolume":"         2","_id":"457","title":"Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity","abstract":[{"lang":"eng","text":"Temperate bacteriophages integrate in bacterial genomes as prophages and represent an important source of genetic variation for bacterial evolution, frequently transmitting fitness-augmenting genes such as toxins responsible for virulence of major pathogens. However, only a fraction of bacteriophage infections are lysogenic and lead to prophage acquisition, whereas the majority are lytic and kill the infected bacteria. Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity to bacteriophages are expected to act as a double-edged sword and increase the odds of survival at the cost of depriving bacteria of potentially beneficial prophages. We show that although restriction-modification systems as mechanisms of innate immunity prevent both lytic and lysogenic infections indiscriminately in individual bacteria, they increase the number of prophage-acquiring individuals at the population level. We find that this counterintuitive result is a consequence of phage-host population dynamics, in which restriction-modification systems delay infection onset until bacteria reach densities at which the probability of lysogeny increases. These results underscore the importance of population-level dynamics as a key factor modulating costs and benefits of immunity to temperate bacteriophages"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1"},{"author":[{"first_name":"Simona","full_name":"Colabrese, Simona","last_name":"Colabrese"},{"first_name":"Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","full_name":"De Martino, Daniele","last_name":"De Martino","orcid":"0000-0002-5214-4706"},{"first_name":"Luca","full_name":"Leuzzi, Luca","last_name":"Leuzzi"},{"last_name":"Marinari","full_name":"Marinari, Enzo","first_name":"Enzo"}],"day":"26","publication_status":"published","publist_id":"6826","date_created":"2018-12-11T11:48:41Z","language":[{"iso":"eng"}],"year":"2017","department":[{"_id":"GaTk"}],"project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"type":"journal_article","date_published":"2017-09-26T00:00:00Z","volume":2017,"external_id":{"isi":["000411842900001"]},"oa_version":"Submitted Version","date_updated":"2023-09-26T16:18:12Z","doi":"10.1088/1742-5468/aa85c3","publisher":"IOPscience","publication":" Journal of Statistical Mechanics: Theory and Experiment","article_processing_charge":"No","quality_controlled":"1","oa":1,"article_number":"093404","month":"09","issue":"9","publication_identifier":{"issn":["17425468"]},"scopus_import":"1","isi":1,"status":"public","ec_funded":1,"intvolume":"      2017","citation":{"short":"S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari,  Journal of Statistical Mechanics: Theory and Experiment 2017 (2017).","ieee":"S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions in integer linear problems,” <i> Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2017, no. 9. IOPscience, 2017.","apa":"Colabrese, S., De Martino, D., Leuzzi, L., &#38; Marinari, E. (2017). Phase transitions in integer linear problems. <i> Journal of Statistical Mechanics: Theory and Experiment</i>. IOPscience. <a href=\"https://doi.org/10.1088/1742-5468/aa85c3\">https://doi.org/10.1088/1742-5468/aa85c3</a>","ista":"Colabrese S, De Martino D, Leuzzi L, Marinari E. 2017. Phase transitions in integer linear problems.  Journal of Statistical Mechanics: Theory and Experiment. 2017(9), 093404.","chicago":"Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari. “Phase Transitions in Integer Linear Problems.” <i> Journal of Statistical Mechanics: Theory and Experiment</i>. IOPscience, 2017. <a href=\"https://doi.org/10.1088/1742-5468/aa85c3\">https://doi.org/10.1088/1742-5468/aa85c3</a>.","mla":"Colabrese, Simona, et al. “Phase Transitions in Integer Linear Problems.” <i> Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2017, no. 9, 093404, IOPscience, 2017, doi:<a href=\"https://doi.org/10.1088/1742-5468/aa85c3\">10.1088/1742-5468/aa85c3</a>.","ama":"Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer linear problems. <i> Journal of Statistical Mechanics: Theory and Experiment</i>. 2017;2017(9). doi:<a href=\"https://doi.org/10.1088/1742-5468/aa85c3\">10.1088/1742-5468/aa85c3</a>"},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1705.06303"}],"title":"Phase transitions in integer linear problems","_id":"823","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"text":"The resolution of a linear system with positive integer variables is a basic yet difficult computational problem with many applications. We consider sparse uncorrelated random systems parametrised by the density c and the ratio α=N/M between number of variables N and number of constraints M. By means of ensemble calculations we show that the space of feasible solutions endows a Van-Der-Waals phase diagram in the plane (c, α). We give numerical evidence that the associated computational problems become more difficult across the critical point and in particular in the coexistence region.","lang":"eng"}]},{"issue":"9","publication_identifier":{"issn":["1553734X"]},"scopus_import":1,"file_date_updated":"2020-07-14T12:47:53Z","status":"public","intvolume":"        13","citation":{"chicago":"Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” <i>PLoS Computational Biology</i>. Public Library of Science, 2017. <a href=\"https://doi.org/10.1371/journal.pcbi.1005763\">https://doi.org/10.1371/journal.pcbi.1005763</a>.","mla":"Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” <i>PLoS Computational Biology</i>, vol. 13, no. 9, e1005763, Public Library of Science, 2017, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005763\">10.1371/journal.pcbi.1005763</a>.","ama":"Humplik J, Tkačik G. Probabilistic models for neural populations that naturally capture global coupling and criticality. <i>PLoS Computational Biology</i>. 2017;13(9). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005763\">10.1371/journal.pcbi.1005763</a>","ieee":"J. Humplik and G. Tkačik, “Probabilistic models for neural populations that naturally capture global coupling and criticality,” <i>PLoS Computational Biology</i>, vol. 13, no. 9. Public Library of Science, 2017.","short":"J. Humplik, G. Tkačik, PLoS Computational Biology 13 (2017).","apa":"Humplik, J., &#38; Tkačik, G. (2017). Probabilistic models for neural populations that naturally capture global coupling and criticality. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005763\">https://doi.org/10.1371/journal.pcbi.1005763</a>","ista":"Humplik J, Tkačik G. 2017. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 13(9), e1005763."},"has_accepted_license":"1","title":"Probabilistic models for neural populations that naturally capture global coupling and criticality","_id":"720","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality."}],"author":[{"last_name":"Humplik","full_name":"Humplik, Jan","first_name":"Jan","id":"2E9627A8-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik","orcid":"0000-0002-6699-1455"}],"pubrep_id":"884","day":"19","publication_status":"published","publist_id":"6960","date_created":"2018-12-11T11:48:08Z","year":"2017","language":[{"iso":"eng"}],"ddc":["530","571"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"GaTk"}],"date_published":"2017-09-19T00:00:00Z","type":"journal_article","project":[{"name":"Information processing and computation in fish groups","_id":"255008E4-B435-11E9-9278-68D0E5697425","grant_number":"RGP0065/2012"},{"_id":"254D1A94-B435-11E9-9278-68D0E5697425","grant_number":"P 25651-N26","name":"Sensitivity to higher-order statistics in natural scenes","call_identifier":"FWF"}],"volume":13,"oa_version":"Published Version","publisher":"Public Library of Science","doi":"10.1371/journal.pcbi.1005763","date_updated":"2021-01-12T08:12:21Z","publication":"PLoS Computational Biology","article_processing_charge":"Yes","oa":1,"quality_controlled":"1","file":[{"access_level":"open_access","file_name":"IST-2017-884-v1+1_journal.pcbi.1005763.pdf","checksum":"81107096c19771c36ddbe6f0282a3acb","date_updated":"2020-07-14T12:47:53Z","file_size":14167050,"content_type":"application/pdf","date_created":"2018-12-12T10:18:30Z","file_id":"5352","relation":"main_file","creator":"system"}],"article_number":"e1005763","month":"09"},{"citation":{"chicago":"Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” <i>PNAS</i>. National Academy of Sciences, 2017. <a href=\"https://doi.org/10.1073/pnas.1703817114\">https://doi.org/10.1073/pnas.1703817114</a>.","mla":"Harpaz, Roy, et al. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” <i>PNAS</i>, vol. 114, no. 38, National Academy of Sciences, 2017, pp. 10149–54, doi:<a href=\"https://doi.org/10.1073/pnas.1703817114\">10.1073/pnas.1703817114</a>.","ama":"Harpaz R, Tkačik G, Schneidman E. Discrete modes of social information processing predict individual behavior of fish in a group. <i>PNAS</i>. 2017;114(38):10149-10154. doi:<a href=\"https://doi.org/10.1073/pnas.1703817114\">10.1073/pnas.1703817114</a>","ieee":"R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information processing predict individual behavior of fish in a group,” <i>PNAS</i>, vol. 114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017.","short":"R. Harpaz, G. Tkačik, E. Schneidman, PNAS 114 (2017) 10149–10154.","apa":"Harpaz, R., Tkačik, G., &#38; Schneidman, E. (2017). Discrete modes of social information processing predict individual behavior of fish in a group. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1703817114\">https://doi.org/10.1073/pnas.1703817114</a>","ista":"Harpaz R, Tkačik G, Schneidman E. 2017. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 114(38), 10149–10154."},"intvolume":"       114","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617265/","open_access":"1"}],"status":"public","pmid":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"Individual computations and social interactions underlying collective behavior in groups of animals are of great ethological, behavioral, and theoretical interest. While complex individual behaviors have successfully been parsed into small dictionaries of stereotyped behavioral modes, studies of collective behavior largely ignored these findings; instead, their focus was on inferring single, mode-independent social interaction rules that reproduced macroscopic and often qualitative features of group behavior. Here, we bring these two approaches together to predict individual swimming patterns of adult zebrafish in a group. We show that fish alternate between an “active” mode, in which they are sensitive to the swimming patterns of conspecifics, and a “passive” mode, where they ignore them. Using a model that accounts for these two modes explicitly, we predict behaviors of individual fish with high accuracy, outperforming previous approaches that assumed a single continuous computation by individuals and simple metric or topological weighing of neighbors’ behavior. At the group level, switching between active and passive modes is uncorrelated among fish, but correlated directional swimming behavior still emerges. Our quantitative approach for studying complex, multi-modal individual behavior jointly with emergent group behavior is readily extensible to additional behavioral modes and their neural correlates as well as to other species."}],"title":"Discrete modes of social information processing predict individual behavior of fish in a group","_id":"725","publication_identifier":{"issn":["00278424"]},"issue":"38","scopus_import":1,"external_id":{"pmid":["28874581"]},"oa_version":"Submitted Version","type":"journal_article","date_published":"2017-09-19T00:00:00Z","volume":114,"month":"09","quality_controlled":"1","oa":1,"publisher":"National Academy of Sciences","doi":"10.1073/pnas.1703817114","date_updated":"2021-01-12T08:12:36Z","publication":"PNAS","date_created":"2018-12-11T11:48:10Z","day":"19","publist_id":"6953","publication_status":"published","author":[{"last_name":"Harpaz","full_name":"Harpaz, Roy","first_name":"Roy"},{"orcid":"0000-0002-6699-1455","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper","full_name":"Tkacik, Gasper"},{"last_name":"Schneidman","first_name":"Elad","full_name":"Schneidman, Elad"}],"page":"10149 - 10154","department":[{"_id":"GaTk"}],"year":"2017","language":[{"iso":"eng"}]},{"publication_identifier":{"issn":["09594388"]},"scopus_import":"1","isi":1,"intvolume":"        46","citation":{"apa":"Savin, C., &#38; Tkačik, G. (2017). Maximum entropy models as a tool for building precise neural controls. <i>Current Opinion in Neurobiology</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.conb.2017.08.001\">https://doi.org/10.1016/j.conb.2017.08.001</a>","ista":"Savin C, Tkačik G. 2017. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 46, 120–126.","ieee":"C. Savin and G. Tkačik, “Maximum entropy models as a tool for building precise neural controls,” <i>Current Opinion in Neurobiology</i>, vol. 46. Elsevier, pp. 120–126, 2017.","short":"C. Savin, G. Tkačik, Current Opinion in Neurobiology 46 (2017) 120–126.","mla":"Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” <i>Current Opinion in Neurobiology</i>, vol. 46, Elsevier, 2017, pp. 120–26, doi:<a href=\"https://doi.org/10.1016/j.conb.2017.08.001\">10.1016/j.conb.2017.08.001</a>.","ama":"Savin C, Tkačik G. Maximum entropy models as a tool for building precise neural controls. <i>Current Opinion in Neurobiology</i>. 2017;46:120-126. doi:<a href=\"https://doi.org/10.1016/j.conb.2017.08.001\">10.1016/j.conb.2017.08.001</a>","chicago":"Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” <i>Current Opinion in Neurobiology</i>. Elsevier, 2017. <a href=\"https://doi.org/10.1016/j.conb.2017.08.001\">https://doi.org/10.1016/j.conb.2017.08.001</a>."},"status":"public","ec_funded":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"text":"Neural responses are highly structured, with population activity restricted to a small subset of the astronomical range of possible activity patterns. Characterizing these statistical regularities is important for understanding circuit computation, but challenging in practice. Here we review recent approaches based on the maximum entropy principle used for quantifying collective behavior in neural activity. We highlight recent models that capture population-level statistics of neural data, yielding insights into the organization of the neural code and its biological substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing surrogate ensembles that preserve aspects of the data, but are otherwise maximally unstructured. This idea can be used to generate a hierarchy of controls against which rigorous statistical tests are possible.","lang":"eng"}],"title":"Maximum entropy models as a tool for building precise neural controls","_id":"730","date_created":"2018-12-11T11:48:11Z","day":"01","publication_status":"published","publist_id":"6943","author":[{"id":"3933349E-F248-11E8-B48F-1D18A9856A87","first_name":"Cristina","full_name":"Savin, Cristina","last_name":"Savin"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper","last_name":"Tkacik","orcid":"0000-0002-6699-1455"}],"page":"120 - 126","department":[{"_id":"GaTk"}],"year":"2017","language":[{"iso":"eng"}],"oa_version":"None","external_id":{"isi":["000416196400016"]},"project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"date_published":"2017-10-01T00:00:00Z","type":"journal_article","volume":46,"month":"10","quality_controlled":"1","article_processing_charge":"No","publisher":"Elsevier","doi":"10.1016/j.conb.2017.08.001","date_updated":"2023-09-28T11:32:22Z","publication":"Current Opinion in Neurobiology"},{"day":"23","publist_id":"6934","publication_status":"published","date_created":"2018-12-11T11:48:13Z","page":"198 - 211","author":[{"full_name":"Barone, Vanessa","first_name":"Vanessa","id":"419EECCC-F248-11E8-B48F-1D18A9856A87","last_name":"Barone","orcid":"0000-0003-2676-3367"},{"id":"29E0800A-F248-11E8-B48F-1D18A9856A87","first_name":"Moritz","full_name":"Lang, Moritz","last_name":"Lang"},{"full_name":"Krens, Gabriel","first_name":"Gabriel","id":"2B819732-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4761-5996","last_name":"Krens"},{"first_name":"Saurabh","full_name":"Pradhan, Saurabh","last_name":"Pradhan"},{"id":"40B34FE2-F248-11E8-B48F-1D18A9856A87","first_name":"Shayan","full_name":"Shamipour, Shayan","last_name":"Shamipour"},{"id":"3BED66BE-F248-11E8-B48F-1D18A9856A87","first_name":"Keisuke","full_name":"Sako, Keisuke","last_name":"Sako","orcid":"0000-0002-6453-8075"},{"last_name":"Sikora","full_name":"Sikora, Mateusz K","first_name":"Mateusz K","id":"2F74BCDE-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet"},{"id":"39427864-F248-11E8-B48F-1D18A9856A87","first_name":"Carl-Philipp J","full_name":"Heisenberg, Carl-Philipp J","last_name":"Heisenberg","orcid":"0000-0002-0912-4566"}],"department":[{"_id":"CaHe"},{"_id":"CaGu"},{"_id":"GaTk"}],"related_material":{"record":[{"id":"961","relation":"dissertation_contains","status":"public"},{"id":"8350","status":"public","relation":"dissertation_contains"}]},"year":"2017","language":[{"iso":"eng"}],"oa_version":"None","external_id":{"isi":["000413443700011"]},"date_published":"2017-10-23T00:00:00Z","type":"journal_article","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"},{"grant_number":"I2058","_id":"252DD2A6-B435-11E9-9278-68D0E5697425","name":"Cell segregation in gastrulation: the role of cell fate specification","call_identifier":"FWF"}],"volume":43,"quality_controlled":"1","month":"10","date_updated":"2024-03-25T23:30:21Z","doi":"10.1016/j.devcel.2017.09.014","publisher":"Cell Press","publication":"Developmental Cell","article_processing_charge":"No","publication_identifier":{"issn":["15345807"]},"issue":"2","scopus_import":"1","isi":1,"citation":{"short":"V. Barone, M. Lang, G. Krens, S. Pradhan, S. Shamipour, K. Sako, M.K. Sikora, C.C. Guet, C.-P.J. Heisenberg, Developmental Cell 43 (2017) 198–211.","ieee":"V. Barone <i>et al.</i>, “An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate,” <i>Developmental Cell</i>, vol. 43, no. 2. Cell Press, pp. 198–211, 2017.","apa":"Barone, V., Lang, M., Krens, G., Pradhan, S., Shamipour, S., Sako, K., … Heisenberg, C.-P. J. (2017). An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. <i>Developmental Cell</i>. Cell Press. <a href=\"https://doi.org/10.1016/j.devcel.2017.09.014\">https://doi.org/10.1016/j.devcel.2017.09.014</a>","ista":"Barone V, Lang M, Krens G, Pradhan S, Shamipour S, Sako K, Sikora MK, Guet CC, Heisenberg C-PJ. 2017. An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. Developmental Cell. 43(2), 198–211.","chicago":"Barone, Vanessa, Moritz Lang, Gabriel Krens, Saurabh Pradhan, Shayan Shamipour, Keisuke Sako, Mateusz K Sikora, Calin C Guet, and Carl-Philipp J Heisenberg. “An Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling Determines Cell Fate.” <i>Developmental Cell</i>. Cell Press, 2017. <a href=\"https://doi.org/10.1016/j.devcel.2017.09.014\">https://doi.org/10.1016/j.devcel.2017.09.014</a>.","mla":"Barone, Vanessa, et al. “An Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling Determines Cell Fate.” <i>Developmental Cell</i>, vol. 43, no. 2, Cell Press, 2017, pp. 198–211, doi:<a href=\"https://doi.org/10.1016/j.devcel.2017.09.014\">10.1016/j.devcel.2017.09.014</a>.","ama":"Barone V, Lang M, Krens G, et al. An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. <i>Developmental Cell</i>. 2017;43(2):198-211. doi:<a href=\"https://doi.org/10.1016/j.devcel.2017.09.014\">10.1016/j.devcel.2017.09.014</a>"},"intvolume":"        43","status":"public","ec_funded":1,"title":"An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate","_id":"735","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"lang":"eng","text":"Cell-cell contact formation constitutes an essential step in evolution, leading to the differentiation of specialized cell types. However, remarkably little is known about whether and how the interplay between contact formation and fate specification affects development. Here, we identify a positive feedback loop between cell-cell contact duration, morphogen signaling, and mesendoderm cell-fate specification during zebrafish gastrulation. We show that long-lasting cell-cell contacts enhance the competence of prechordal plate (ppl) progenitor cells to respond to Nodal signaling, required for ppl cell-fate specification. We further show that Nodal signaling promotes ppl cell-cell contact duration, generating a positive feedback loop between ppl cell-cell contact duration and cell-fate specification. Finally, by combining mathematical modeling and experimentation, we show that this feedback determines whether anterior axial mesendoderm cells become ppl or, instead, turn into endoderm. Thus, the interdependent activities of cell-cell signaling and contact formation control fate diversification within the developing embryo."}]},{"publication_identifier":{"issn":["03036898"]},"issue":"2","isi":1,"scopus_import":"1","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1410.1242"}],"citation":{"short":"A. Martin Del Campo Sanchez, S.A. Cepeda Humerez, C. Uhler, Scandinavian Journal of Statistics 44 (2017) 285–306.","ieee":"A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit testing for the Ising model,” <i>Scandinavian Journal of Statistics</i>, vol. 44, no. 2. Wiley-Blackwell, pp. 285–306, 2017.","apa":"Martin Del Campo Sanchez, A., Cepeda Humerez, S. A., &#38; Uhler, C. (2017). Exact goodness-of-fit testing for the Ising model. <i>Scandinavian Journal of Statistics</i>. Wiley-Blackwell. <a href=\"https://doi.org/10.1111/sjos.12251\">https://doi.org/10.1111/sjos.12251</a>","ista":"Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. 2017. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 44(2), 285–306.","chicago":"Martin Del Campo Sanchez, Abraham, Sarah A Cepeda Humerez, and Caroline Uhler. “Exact Goodness-of-Fit Testing for the Ising Model.” <i>Scandinavian Journal of Statistics</i>. Wiley-Blackwell, 2017. <a href=\"https://doi.org/10.1111/sjos.12251\">https://doi.org/10.1111/sjos.12251</a>.","mla":"Martin Del Campo Sanchez, Abraham, et al. “Exact Goodness-of-Fit Testing for the Ising Model.” <i>Scandinavian Journal of Statistics</i>, vol. 44, no. 2, Wiley-Blackwell, 2017, pp. 285–306, doi:<a href=\"https://doi.org/10.1111/sjos.12251\">10.1111/sjos.12251</a>.","ama":"Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. Exact goodness-of-fit testing for the Ising model. <i>Scandinavian Journal of Statistics</i>. 2017;44(2):285-306. doi:<a href=\"https://doi.org/10.1111/sjos.12251\">10.1111/sjos.12251</a>"},"intvolume":"        44","status":"public","abstract":[{"lang":"eng","text":"The Ising model is one of the simplest and most famous models of interacting systems. It was originally proposed to model ferromagnetic interactions in statistical physics and is now widely used to model spatial processes in many areas such as ecology, sociology, and genetics, usually without testing its goodness-of-fit. Here, we propose an exact goodness-of-fit test for the finite-lattice Ising model. The theory of Markov bases has been developed in algebraic statistics for exact goodness-of-fit testing using a Monte Carlo approach. However, this beautiful theory has fallen short of its promise for applications, because finding a Markov basis is usually computationally intractable. We develop a Monte Carlo method for exact goodness-of-fit testing for the Ising model which avoids computing a Markov basis and also leads to a better connectivity of the Markov chain and hence to a faster convergence. We show how this method can be applied to analyze the spatial organization of receptors on the cell membrane."}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"2016","title":"Exact goodness-of-fit testing for the Ising model","arxiv":1,"date_created":"2018-12-11T11:55:13Z","publication_status":"published","publist_id":"5060","day":"01","author":[{"last_name":"Martin Del Campo Sanchez","first_name":"Abraham","full_name":"Martin Del Campo Sanchez, Abraham"},{"full_name":"Cepeda Humerez, Sarah A","first_name":"Sarah A","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","last_name":"Cepeda Humerez"},{"orcid":"0000-0002-7008-0216","last_name":"Uhler","full_name":"Uhler, Caroline","id":"49ADD78E-F248-11E8-B48F-1D18A9856A87","first_name":"Caroline"}],"page":"285 - 306","department":[{"_id":"GaTk"}],"year":"2017","language":[{"iso":"eng"}],"related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"6473"}]},"external_id":{"arxiv":["1410.1242"],"isi":["000400985000001"]},"oa_version":"Preprint","volume":44,"date_published":"2017-06-01T00:00:00Z","type":"journal_article","month":"06","oa":1,"quality_controlled":"1","article_processing_charge":"No","publication":"Scandinavian Journal of Statistics","doi":"10.1111/sjos.12251","publisher":"Wiley-Blackwell","date_updated":"2023-09-19T15:13:27Z"},{"scopus_import":"1","issue":"6","publication_identifier":{"issn":["2470-0045"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region.","lang":"eng"}],"title":"Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes","_id":"548","status":"public","ec_funded":1,"citation":{"ama":"De Martino D. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. <i>Physical Review E</i>. 2017;96(6). doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.060401\">10.1103/PhysRevE.96.060401</a>","mla":"De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” <i>Physical Review E</i>, vol. 96, no. 6, 060401, American Physical Society, 2017, doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.060401\">10.1103/PhysRevE.96.060401</a>.","chicago":"De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” <i>Physical Review E</i>. American Physical Society, 2017. <a href=\"https://doi.org/10.1103/PhysRevE.96.060401\">https://doi.org/10.1103/PhysRevE.96.060401</a>.","ista":"De Martino D. 2017. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 96(6), 060401.","apa":"De Martino, D. (2017). Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. <i>Physical Review E</i>. American Physical Society. <a href=\"https://doi.org/10.1103/PhysRevE.96.060401\">https://doi.org/10.1103/PhysRevE.96.060401</a>","ieee":"D. De Martino, “Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes,” <i>Physical Review E</i>, vol. 96, no. 6. American Physical Society, 2017.","short":"D. De Martino, Physical Review E 96 (2017)."},"intvolume":"        96","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1707.00320"}],"year":"2017","language":[{"iso":"eng"}],"department":[{"_id":"GaTk"}],"author":[{"orcid":"0000-0002-5214-4706","last_name":"De Martino","first_name":"Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","full_name":"De Martino, Daniele"}],"alternative_title":["Rapid Communications"],"date_created":"2018-12-11T11:47:06Z","day":"21","publist_id":"7266","publication_status":"published","article_processing_charge":"No","date_updated":"2023-10-10T13:29:38Z","doi":"10.1103/PhysRevE.96.060401","publisher":"American Physical Society","publication":"Physical Review E","month":"12","oa":1,"quality_controlled":"1","article_number":"060401","type":"journal_article","date_published":"2017-12-21T00:00:00Z","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"volume":96,"oa_version":"Submitted Version"},{"day":"10","date_created":"2018-12-12T12:31:32Z","datarep_id":"53","author":[{"full_name":"Bergmiller, Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","last_name":"Bergmiller","orcid":"0000-0001-5396-4346"},{"orcid":"0000-0003-2912-6769","last_name":"Andersson","full_name":"Andersson, Anna M","id":"2B8A40DA-F248-11E8-B48F-1D18A9856A87","first_name":"Anna M"},{"orcid":"0000-0003-3768-877X","last_name":"Tomasek","full_name":"Tomasek, Kathrin","first_name":"Kathrin","id":"3AEC8556-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Balleza","full_name":"Balleza, Enrique","first_name":"Enrique"},{"first_name":"Daniel","full_name":"Kiviet, Daniel","last_name":"Kiviet"},{"last_name":"Hauschild","orcid":"0000-0001-9843-3522","full_name":"Hauschild, Robert","first_name":"Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","orcid":"0000-0002-6699-1455","last_name":"Tkacik"},{"last_name":"Guet","orcid":"0000-0001-6220-2052","first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C"}],"keyword":["single cell microscopy","mother machine microfluidic device","AcrAB-TolC pump","multi-drug efflux","Escherichia coli"],"tmp":{"short":"CC0 (1.0)","name":"Creative Commons Public Domain Dedication (CC0 1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode"},"file_date_updated":"2020-07-14T12:47:03Z","department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"Bio"}],"related_material":{"record":[{"status":"public","relation":"research_paper","id":"665"}]},"ddc":["571"],"year":"2017","citation":{"chicago":"Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity.” Institute of Science and Technology Austria, 2017. <a href=\"https://doi.org/10.15479/AT:ISTA:53\">https://doi.org/10.15479/AT:ISTA:53</a>.","ama":"Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. 2017. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:53\">10.15479/AT:ISTA:53</a>","mla":"Bergmiller, Tobias, et al. <i>Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity</i>. Institute of Science and Technology Austria, 2017, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:53\">10.15479/AT:ISTA:53</a>.","ieee":"T. Bergmiller <i>et al.</i>, “Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity.” Institute of Science and Technology Austria, 2017.","short":"T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, (2017).","ista":"Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik G, Guet CC. 2017. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:53\">10.15479/AT:ISTA:53</a>.","apa":"Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:53\">https://doi.org/10.15479/AT:ISTA:53</a>"},"has_accepted_license":"1","oa_version":"Published Version","status":"public","date_published":"2017-03-10T00:00:00Z","type":"research_data","oa":1,"file":[{"file_name":"IST-2017-53-v1+1_Data_MDE.zip","access_level":"open_access","checksum":"d77859af757ac8025c50c7b12b52eaf3","date_updated":"2020-07-14T12:47:03Z","file_size":6773204,"content_type":"application/zip","date_created":"2018-12-12T13:02:38Z","file_id":"5603","creator":"system","relation":"main_file"}],"month":"03","doi":"10.15479/AT:ISTA:53","title":"Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity","publisher":"Institute of Science and Technology Austria","date_updated":"2024-02-21T13:49:00Z","_id":"5560","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"This repository contains the data collected for the manuscript \"Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity\".\r\nThe data is compressed into a single archive. Within the archive, different folders correspond to figures of the main text and the SI of the related publication.\r\nData is saved as plain text, with each folder containing a separate readme file describing the format. Typically, the data is from fluorescence microscopy measurements of single cells growing in a microfluidic \"mother machine\" device, and consists of relevant values (primarily arbitrary unit or normalized fluorescence measurements, and division times / growth rates) after raw microscopy images have been processed, segmented, and their features extracted, as described in the methods section of the related publication."}]},{"related_material":{"record":[{"id":"2257","relation":"research_paper","status":"public"}]},"year":"2017","ddc":["570"],"file_date_updated":"2020-07-14T12:47:03Z","tmp":{"short":"CC0 (1.0)","name":"Creative Commons Public Domain Dedication (CC0 1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode"},"department":[{"_id":"GaTk"}],"keyword":["multi-electrode recording","retinal ganglion cells"],"author":[{"full_name":"Marre, Olivier","first_name":"Olivier","last_name":"Marre"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper","full_name":"Tkacik, Gasper","orcid":"0000-0002-6699-1455","last_name":"Tkacik"},{"first_name":"Dario","full_name":"Amodei, Dario","last_name":"Amodei"},{"full_name":"Schneidman, Elad","first_name":"Elad","last_name":"Schneidman"},{"full_name":"Bialek, William","first_name":"William","last_name":"Bialek"},{"last_name":"Berry","full_name":"Berry, Michael","first_name":"Michael"}],"datarep_id":"61","date_created":"2018-12-12T12:31:33Z","day":"27","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"This data was collected as part of the study [1]. It consists of preprocessed multi-electrode array recording from 160 salamander retinal ganglion cells responding to 297 repeats of a 19 s natural movie. The data is available in two formats: (1) a .mat file containing an array with dimensions “number of repeats” x “number of neurons” x “time in a repeat”; (2) a zipped .txt file containing the same data represented as an array with dimensions “number of neurons” x “number of samples”, where the number of samples is equal to the product of the number of repeats and timebins within a repeat. The time dimension is divided into 20 ms time windows, and the array is binary indicating whether a given cell elicited at least one spike in a given time window during a particular repeat. See the reference below for details regarding collection and preprocessing:\r\n\r\n[1] Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry MJ II. Searching for Collective Behavior in a Large Network of Sensory Neurons. PLoS Comput Biol. 2014;10(1):e1003408.","lang":"eng"}],"publisher":"Institute of Science and Technology Austria","doi":"10.15479/AT:ISTA:61","title":"Multi-electrode array recording from salamander retinal ganglion cells","date_updated":"2024-02-21T13:46:14Z","_id":"5562","month":"02","oa":1,"file":[{"creator":"system","relation":"main_file","content_type":"application/octet-stream","file_id":"5622","date_created":"2018-12-12T13:03:04Z","date_updated":"2020-07-14T12:47:03Z","file_size":1336936,"access_level":"open_access","file_name":"IST-2017-61-v1+1_bint_fishmovie32_100.mat","checksum":"e620eff260646f57b479a69492c8b765"},{"date_created":"2018-12-12T13:03:05Z","file_id":"5623","content_type":"application/zip","creator":"system","relation":"main_file","checksum":"de83f9b81ea0aae3cddfc3ed982e0759","access_level":"open_access","file_name":"IST-2017-61-v1+2_bint_fishmovie32_100.zip","file_size":1897543,"date_updated":"2020-07-14T12:47:03Z"}],"date_published":"2017-02-27T00:00:00Z","type":"research_data","status":"public","oa_version":"Published Version","citation":{"chicago":"Marre, Olivier, Gašper Tkačik, Dario Amodei, Elad Schneidman, William Bialek, and Michael Berry. “Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells.” Institute of Science and Technology Austria, 2017. <a href=\"https://doi.org/10.15479/AT:ISTA:61\">https://doi.org/10.15479/AT:ISTA:61</a>.","ama":"Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. Multi-electrode array recording from salamander retinal ganglion cells. 2017. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:61\">10.15479/AT:ISTA:61</a>","mla":"Marre, Olivier, et al. <i>Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells</i>. Institute of Science and Technology Austria, 2017, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:61\">10.15479/AT:ISTA:61</a>.","short":"O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, M. Berry, (2017).","ieee":"O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Multi-electrode array recording from salamander retinal ganglion cells.” Institute of Science and Technology Austria, 2017.","ista":"Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. 2017. Multi-electrode array recording from salamander retinal ganglion cells, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:61\">10.15479/AT:ISTA:61</a>.","apa":"Marre, O., Tkačik, G., Amodei, D., Schneidman, E., Bialek, W., &#38; Berry, M. (2017). Multi-electrode array recording from salamander retinal ganglion cells. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:61\">https://doi.org/10.15479/AT:ISTA:61</a>"},"has_accepted_license":"1"},{"ec_funded":1,"status":"public","has_accepted_license":"1","citation":{"mla":"Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” <i>Nature Communications</i>, vol. 8, no. 1, 1535, Nature Publishing Group, 2017, doi:<a href=\"https://doi.org/10.1038/s41467-017-01683-1\">10.1038/s41467-017-01683-1</a>.","ama":"Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population behavior through computer interfaced control of individual cells. <i>Nature Communications</i>. 2017;8(1). doi:<a href=\"https://doi.org/10.1038/s41467-017-01683-1\">10.1038/s41467-017-01683-1</a>","chicago":"Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” <i>Nature Communications</i>. Nature Publishing Group, 2017. <a href=\"https://doi.org/10.1038/s41467-017-01683-1\">https://doi.org/10.1038/s41467-017-01683-1</a>.","apa":"Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., &#38; Guet, C. C. (2017). Shaping bacterial population behavior through computer interfaced control of individual cells. <i>Nature Communications</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/s41467-017-01683-1\">https://doi.org/10.1038/s41467-017-01683-1</a>","ista":"Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 8(1), 1535.","short":"R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications 8 (2017).","ieee":"R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping bacterial population behavior through computer interfaced control of individual cells,” <i>Nature Communications</i>, vol. 8, no. 1. Nature Publishing Group, 2017."},"intvolume":"         8","_id":"613","title":"Shaping bacterial population behavior through computer interfaced control of individual cells","abstract":[{"text":"Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.","lang":"eng"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","acknowledgement":"We are grateful to M. Lang, H. Janovjak, M. Khammash, A. Milias-Argeitis, M. Rullan, G. Batt, A. Bosma-Moody, Aryan, S. Leibler, and members of the Guet and Tkačik groups for helpful discussion, comments, and suggestions. We thank A. Moglich, T. Mathes, J. Tabor, and S. Schmidl for kind gifts of strains, and R. Hauschild, B. Knep, M. Lang, T. Asenov, E. Papusheva, T. Menner, T. Adletzberger, and J. Merrin for technical assistance. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. (to R.C. and J.R.), Austrian Science Fund grant FWF P28844 (to G.T.), and internal IST Austria Interdisciplinary Project Support. J.R. acknowledges support from the Agence Nationale de la Recherche (ANR) under Grant Nos. ANR-16-CE33-0018 (MEMIP), ANR-16-CE12-0025 (COGEX) and ANR-10-BINF-06-01 (ICEBERG).","issue":"1","publication_identifier":{"issn":["20411723"]},"scopus_import":1,"file_date_updated":"2020-07-14T12:47:20Z","volume":8,"type":"journal_article","project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"},{"name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"date_published":"2017-12-01T00:00:00Z","oa_version":"Published Version","publication":"Nature Communications","doi":"10.1038/s41467-017-01683-1","date_updated":"2021-01-12T08:06:15Z","publisher":"Nature Publishing Group","article_processing_charge":"Yes (in subscription journal)","article_number":"1535","oa":1,"file":[{"date_created":"2018-12-12T10:16:05Z","file_id":"5190","content_type":"application/pdf","creator":"system","relation":"main_file","checksum":"44bb5d0229926c23a9955d9fe0f9723f","file_name":"IST-2017-911-v1+1_s41467-017-01683-1.pdf","access_level":"open_access","file_size":1951699,"date_updated":"2020-07-14T12:47:20Z"}],"quality_controlled":"1","month":"12","pubrep_id":"911","author":[{"last_name":"Chait","orcid":"0000-0003-0876-3187","first_name":"Remy P","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","full_name":"Chait, Remy P"},{"last_name":"Ruess","orcid":"0000-0003-1615-3282","full_name":"Ruess, Jakob","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","first_name":"Jakob"},{"orcid":"0000-0001-5396-4346","last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","full_name":"Bergmiller, Tobias"},{"last_name":"Tkacik","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Guet","orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C","full_name":"Guet, Calin C"}],"publist_id":"7191","publication_status":"published","day":"01","date_created":"2018-12-11T11:47:30Z","year":"2017","ddc":["576","579"],"language":[{"iso":"eng"}],"department":[{"_id":"CaGu"},{"_id":"GaTk"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"}},{"month":"02","quality_controlled":"1","article_number":"7846789","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"We present an approach that enables robots to self-organize their sensorimotor behavior from scratch without providing specific information about neither the robot nor its environment. This is achieved by a simple neural control law that increases the consistency between external sensor dynamics and internal neural dynamics of the utterly simple controller. In this way, the embodiment and the agent-environment coupling are the only source of individual development. We show how an anthropomorphic tendon driven arm-shoulder system develops different behaviors depending on that coupling. For instance: Given a bottle half-filled with water, the arm starts to shake it, driven by the physical response of the water. When attaching a brush, the arm can be manipulated into wiping a table, and when connected to a revolvable wheel it finds out how to rotate it. Thus, the robot may be said to discover the affordances of the world. When allowing two (simulated) humanoid robots to interact physically, they engage into a joint behavior development leading to, for instance, spontaneous cooperation. More social effects are observed if the robots can visually perceive each other. Although, as an observer, it is tempting to attribute an apparent intentionality, there is nothing of the kind put in. As a conclusion, we argue that emergent behavior may be much less rooted in explicit intentions, internal motivations, or specific reward systems than is commonly believed.","lang":"eng"}],"title":"Dynamical self consistency leads to behavioral development and emergent social interactions in robots","date_updated":"2021-01-12T08:07:51Z","doi":"10.1109/DEVLRN.2016.7846789","publisher":"IEEE","_id":"652","oa_version":"None","citation":{"short":"R. Der, G.S. Martius, in:, IEEE, 2017.","ieee":"R. Der and G. S. Martius, “Dynamical self consistency leads to behavioral development and emergent social interactions in robots,” presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France, 2017.","apa":"Der, R., &#38; Martius, G. S. (2017). Dynamical self consistency leads to behavioral development and emergent social interactions in robots. Presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France: IEEE. <a href=\"https://doi.org/10.1109/DEVLRN.2016.7846789\">https://doi.org/10.1109/DEVLRN.2016.7846789</a>","ista":"Der R, Martius GS. 2017. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , 7846789.","chicago":"Der, Ralf, and Georg S Martius. “Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots.” IEEE, 2017. <a href=\"https://doi.org/10.1109/DEVLRN.2016.7846789\">https://doi.org/10.1109/DEVLRN.2016.7846789</a>.","mla":"Der, Ralf, and Georg S. Martius. <i>Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots</i>. 7846789, IEEE, 2017, doi:<a href=\"https://doi.org/10.1109/DEVLRN.2016.7846789\">10.1109/DEVLRN.2016.7846789</a>.","ama":"Der R, Martius GS. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. In: IEEE; 2017. doi:<a href=\"https://doi.org/10.1109/DEVLRN.2016.7846789\">10.1109/DEVLRN.2016.7846789</a>"},"date_published":"2017-02-07T00:00:00Z","type":"conference","status":"public","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"scopus_import":1,"language":[{"iso":"eng"}],"year":"2017","publication_identifier":{"isbn":["978-150905069-7"]},"date_created":"2018-12-11T11:47:43Z","day":"07","publication_status":"published","publist_id":"7100","author":[{"first_name":"Ralf","full_name":"Der, Ralf","last_name":"Der"},{"full_name":"Martius, Georg S","id":"3A276B68-F248-11E8-B48F-1D18A9856A87","first_name":"Georg S","last_name":"Martius"}],"conference":{"start_date":"2016-09-19","name":"ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics ","location":"Cergy-Pontoise, France","end_date":"2016-09-22"}},{"date_published":"2017-03-16T00:00:00Z","type":"journal_article","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"volume":11,"oa_version":"Published Version","article_processing_charge":"Yes","date_updated":"2021-01-12T08:08:04Z","publisher":"Frontiers Research Foundation","doi":"10.3389/fnbot.2017.00008","publication":"Frontiers in Neurorobotics","month":"03","oa":1,"quality_controlled":"1","file":[{"content_type":"application/pdf","date_created":"2018-12-12T10:18:49Z","file_id":"5371","creator":"system","relation":"main_file","access_level":"open_access","file_name":"IST-2017-903-v1+1_fnbot-11-00008.pdf","checksum":"b1bc43f96d1df3313c03032c2a46388d","date_updated":"2020-07-14T12:47:33Z","file_size":8439566}],"article_number":"00008","author":[{"full_name":"Der, Ralf","first_name":"Ralf","last_name":"Der"},{"full_name":"Martius, Georg S","id":"3A276B68-F248-11E8-B48F-1D18A9856A87","first_name":"Georg S","last_name":"Martius"}],"pubrep_id":"903","date_created":"2018-12-11T11:47:45Z","day":"16","publist_id":"7078","publication_status":"published","language":[{"iso":"eng"}],"ddc":["006"],"year":"2017","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"status":"public","ec_funded":1,"intvolume":"        11","citation":{"chicago":"Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” <i>Frontiers in Neurorobotics</i>. Frontiers Research Foundation, 2017. <a href=\"https://doi.org/10.3389/fnbot.2017.00008\">https://doi.org/10.3389/fnbot.2017.00008</a>.","ama":"Der R, Martius GS. Self organized behavior generation for musculoskeletal robots. <i>Frontiers in Neurorobotics</i>. 2017;11(MAR). doi:<a href=\"https://doi.org/10.3389/fnbot.2017.00008\">10.3389/fnbot.2017.00008</a>","mla":"Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” <i>Frontiers in Neurorobotics</i>, vol. 11, no. MAR, 00008, Frontiers Research Foundation, 2017, doi:<a href=\"https://doi.org/10.3389/fnbot.2017.00008\">10.3389/fnbot.2017.00008</a>.","ieee":"R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal robots,” <i>Frontiers in Neurorobotics</i>, vol. 11, no. MAR. Frontiers Research Foundation, 2017.","short":"R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017).","ista":"Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 11(MAR), 00008.","apa":"Der, R., &#38; Martius, G. S. (2017). Self organized behavior generation for musculoskeletal robots. <i>Frontiers in Neurorobotics</i>. Frontiers Research Foundation. <a href=\"https://doi.org/10.3389/fnbot.2017.00008\">https://doi.org/10.3389/fnbot.2017.00008</a>"},"has_accepted_license":"1","user_id":"2EBD1598-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors &quot;waiting&quot; to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.","lang":"eng"}],"title":"Self organized behavior generation for musculoskeletal robots","_id":"658","issue":"MAR","publication_identifier":{"issn":["16625218"]},"scopus_import":1,"file_date_updated":"2020-07-14T12:47:33Z"},{"status":"public","citation":{"apa":"Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. <i>Science</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/science.aaf4762\">https://doi.org/10.1126/science.aaf4762</a>","ista":"Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik G, Guet CC. 2017. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. 356(6335), 311–315.","short":"T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, Science 356 (2017) 311–315.","ieee":"T. Bergmiller <i>et al.</i>, “Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity,” <i>Science</i>, vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315, 2017.","mla":"Bergmiller, Tobias, et al. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” <i>Science</i>, vol. 356, no. 6335, American Association for the Advancement of Science, 2017, pp. 311–15, doi:<a href=\"https://doi.org/10.1126/science.aaf4762\">10.1126/science.aaf4762</a>.","ama":"Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. <i>Science</i>. 2017;356(6335):311-315. doi:<a href=\"https://doi.org/10.1126/science.aaf4762\">10.1126/science.aaf4762</a>","chicago":"Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” <i>Science</i>. American Association for the Advancement of Science, 2017. <a href=\"https://doi.org/10.1126/science.aaf4762\">https://doi.org/10.1126/science.aaf4762</a>."},"intvolume":"       356","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"The molecular mechanisms underlying phenotypic variation in isogenic bacterial populations remain poorly understood.We report that AcrAB-TolC, the main multidrug efflux pump of Escherichia coli, exhibits a strong partitioning bias for old cell poles by a segregation mechanism that is mediated by ternary AcrAB-TolC complex formation. Mother cells inheriting old poles are phenotypically distinct and display increased drug efflux activity relative to daughters. Consequently, we find systematic and long-lived growth differences between mother and daughter cells in the presence of subinhibitory drug concentrations. A simple model for biased partitioning predicts a population structure of long-lived and highly heterogeneous phenotypes. This straightforward mechanism of generating sustained growth rate differences at subinhibitory antibiotic concentrations has implications for understanding the emergence of multidrug resistance in bacteria.","lang":"eng"}],"title":"Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity","_id":"665","issue":"6335","publication_identifier":{"issn":["00368075"]},"scopus_import":1,"type":"journal_article","date_published":"2017-04-21T00:00:00Z","project":[{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation"}],"volume":356,"oa_version":"None","article_type":"original","article_processing_charge":"No","date_updated":"2024-02-21T13:49:00Z","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aaf4762","publication":"Science","month":"04","quality_controlled":"1","author":[{"id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","full_name":"Bergmiller, Tobias","last_name":"Bergmiller","orcid":"0000-0001-5396-4346"},{"last_name":"Andersson","orcid":"0000-0003-2912-6769","id":"2B8A40DA-F248-11E8-B48F-1D18A9856A87","first_name":"Anna M","full_name":"Andersson, Anna M"},{"orcid":"0000-0003-3768-877X","last_name":"Tomasek","full_name":"Tomasek, Kathrin","first_name":"Kathrin","id":"3AEC8556-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Balleza, Enrique","first_name":"Enrique","last_name":"Balleza"},{"first_name":"Daniel","full_name":"Kiviet, Daniel","last_name":"Kiviet"},{"orcid":"0000-0001-9843-3522","last_name":"Hauschild","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","first_name":"Robert","full_name":"Hauschild, Robert"},{"first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik","orcid":"0000-0002-6699-1455"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C","full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet"}],"page":"311 - 315","date_created":"2018-12-11T11:47:48Z","day":"21","publist_id":"7064","publication_status":"published","related_material":{"record":[{"status":"public","relation":"popular_science","id":"5560"}]},"language":[{"iso":"eng"}],"year":"2017","department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"Bio"}]},{"day":"26","publication_status":"published","publist_id":"7061","date_created":"2018-12-11T11:47:48Z","page":"393 - 403","author":[{"last_name":"Mitosch","full_name":"Mitosch, Karin","id":"39B66846-F248-11E8-B48F-1D18A9856A87","first_name":"Karin"},{"last_name":"Rieckh","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","full_name":"Rieckh, Georg"},{"full_name":"Bollenbach, Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","last_name":"Bollenbach","orcid":"0000-0003-4398-476X"}],"pubrep_id":"901","department":[{"_id":"ToBo"},{"_id":"GaTk"}],"tmp":{"image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)"},"related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"818"}]},"year":"2017","ddc":["576","610"],"language":[{"iso":"eng"}],"oa_version":"Published Version","type":"journal_article","date_published":"2017-04-26T00:00:00Z","project":[{"grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Optimality principles in responses to antibiotics"},{"grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions"},{"grant_number":"RGP0042/2013","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","name":"Revealing the fundamental limits of cell growth"}],"volume":4,"oa":1,"file":[{"creator":"system","relation":"main_file","content_type":"application/pdf","file_id":"5041","date_created":"2018-12-12T10:13:54Z","date_updated":"2020-07-14T12:47:35Z","file_size":2438660,"access_level":"open_access","file_name":"IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf","checksum":"04ff20011c3d9a601c514aa999a5fe1a"}],"quality_controlled":"1","month":"04","date_updated":"2023-09-07T12:00:25Z","publisher":"Cell Press","doi":"10.1016/j.cels.2017.03.001","publication":"Cell Systems","article_processing_charge":"Yes (in subscription journal)","publication_identifier":{"issn":["24054712"]},"issue":"4","file_date_updated":"2020-07-14T12:47:35Z","scopus_import":1,"citation":{"short":"K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.","ieee":"K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment,” <i>Cell Systems</i>, vol. 4, no. 4. Cell Press, pp. 393–403, 2017.","ista":"Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 4(4), 393–403.","apa":"Mitosch, K., Rieckh, G., &#38; Bollenbach, M. T. (2017). Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. <i>Cell Systems</i>. Cell Press. <a href=\"https://doi.org/10.1016/j.cels.2017.03.001\">https://doi.org/10.1016/j.cels.2017.03.001</a>","chicago":"Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” <i>Cell Systems</i>. Cell Press, 2017. <a href=\"https://doi.org/10.1016/j.cels.2017.03.001\">https://doi.org/10.1016/j.cels.2017.03.001</a>.","ama":"Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. <i>Cell Systems</i>. 2017;4(4):393-403. doi:<a href=\"https://doi.org/10.1016/j.cels.2017.03.001\">10.1016/j.cels.2017.03.001</a>","mla":"Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” <i>Cell Systems</i>, vol. 4, no. 4, Cell Press, 2017, pp. 393–403, doi:<a href=\"https://doi.org/10.1016/j.cels.2017.03.001\">10.1016/j.cels.2017.03.001</a>."},"intvolume":"         4","has_accepted_license":"1","status":"public","ec_funded":1,"title":"Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment","_id":"666","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"Antibiotics elicit drastic changes in microbial gene expression, including the induction of stress response genes. While certain stress responses are known to “cross-protect” bacteria from other stressors, it is unclear whether cellular responses to antibiotics have a similar protective role. By measuring the genome-wide transcriptional response dynamics of Escherichia coli to four antibiotics, we found that trimethoprim induces a rapid acid stress response that protects bacteria from subsequent exposure to acid. Combining microfluidics with time-lapse imaging to monitor survival and acid stress response in single cells revealed that the noisy expression of the acid resistance operon gadBC correlates with single-cell survival. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. The seemingly random single-cell survival under acid stress can therefore be predicted from gadBC expression and rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap for identifying the molecular mechanisms of single-cell cross-protection between antibiotics and other stressors."}]},{"related_material":{"record":[{"id":"9855","relation":"research_data","status":"public"}]},"language":[{"iso":"eng"}],"ddc":["571"],"year":"2017","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"GaTk"}],"author":[{"orcid":"0000-0001-7782-4436","last_name":"Chalk","full_name":"Chalk, Matthew J","first_name":"Matthew J","id":"2BAAC544-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Masset, Paul","first_name":"Paul","last_name":"Masset"},{"last_name":"Gutkin","full_name":"Gutkin, Boris","first_name":"Boris"},{"last_name":"Denève","first_name":"Sophie","full_name":"Denève, Sophie"}],"pubrep_id":"898","day":"01","publist_id":"7035","publication_status":"published","date_created":"2018-12-11T11:47:53Z","doi":"10.1371/journal.pcbi.1005582","publisher":"Public Library of Science","date_updated":"2023-02-23T14:10:54Z","publication":"PLoS Computational Biology","quality_controlled":"1","oa":1,"file":[{"creator":"system","relation":"main_file","content_type":"application/pdf","file_id":"4645","date_created":"2018-12-12T10:07:47Z","date_updated":"2020-07-14T12:47:40Z","file_size":14555676,"file_name":"IST-2017-898-v1+1_journal.pcbi.1005582.pdf","access_level":"open_access","checksum":"796a1026076af6f4405a47d985bc7b68"}],"article_number":"e1005582","month":"06","date_published":"2017-06-01T00:00:00Z","type":"journal_article","volume":13,"oa_version":"Published Version","scopus_import":1,"file_date_updated":"2020-07-14T12:47:40Z","issue":"6","publication_identifier":{"issn":["1553734X"]},"title":"Sensory noise predicts divisive reshaping of receptive fields","_id":"680","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround suppression. Paradoxically, these highly variable receptive fields go alongside and are in fact required for an invariant representation of external sensory features. In addition to offering a normative account of context-dependent changes in sensory responses, perceptual inference in the presence of signal-dependent noise accounts for ubiquitous features of sensory neurons such as divisive normalization, gain control and contrast dependent temporal dynamics.","lang":"eng"}],"status":"public","intvolume":"        13","citation":{"chicago":"Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” <i>PLoS Computational Biology</i>. Public Library of Science, 2017. <a href=\"https://doi.org/10.1371/journal.pcbi.1005582\">https://doi.org/10.1371/journal.pcbi.1005582</a>.","mla":"Chalk, Matthew J., et al. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” <i>PLoS Computational Biology</i>, vol. 13, no. 6, e1005582, Public Library of Science, 2017, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005582\">10.1371/journal.pcbi.1005582</a>.","ama":"Chalk MJ, Masset P, Gutkin B, Denève S. Sensory noise predicts divisive reshaping of receptive fields. <i>PLoS Computational Biology</i>. 2017;13(6). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005582\">10.1371/journal.pcbi.1005582</a>","ieee":"M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts divisive reshaping of receptive fields,” <i>PLoS Computational Biology</i>, vol. 13, no. 6. Public Library of Science, 2017.","short":"M.J. Chalk, P. Masset, B. Gutkin, S. Denève, PLoS Computational Biology 13 (2017).","apa":"Chalk, M. J., Masset, P., Gutkin, B., &#38; Denève, S. (2017). Sensory noise predicts divisive reshaping of receptive fields. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005582\">https://doi.org/10.1371/journal.pcbi.1005582</a>","ista":"Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 13(6), e1005582."},"has_accepted_license":"1"},{"publication_identifier":{"issn":["0005-1098"]},"file_date_updated":"2018-12-12T10:11:29Z","scopus_import":"1","isi":1,"citation":{"apa":"Lang, M., &#38; Sontag, E. (2017). Zeros of nonlinear systems with input invariances. <i>Automatica</i>. International Federation of Automatic Control. <a href=\"https://doi.org/10.1016/j.automatica.2017.03.030\">https://doi.org/10.1016/j.automatica.2017.03.030</a>","ista":"Lang M, Sontag E. 2017. Zeros of nonlinear systems with input invariances. Automatica. 81C, 46–55.","short":"M. Lang, E. Sontag, Automatica 81C (2017) 46–55.","ieee":"M. Lang and E. Sontag, “Zeros of nonlinear systems with input invariances,” <i>Automatica</i>, vol. 81C. International Federation of Automatic Control, pp. 46–55, 2017.","mla":"Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input Invariances.” <i>Automatica</i>, vol. 81C, International Federation of Automatic Control, 2017, pp. 46–55, doi:<a href=\"https://doi.org/10.1016/j.automatica.2017.03.030\">10.1016/j.automatica.2017.03.030</a>.","ama":"Lang M, Sontag E. Zeros of nonlinear systems with input invariances. <i>Automatica</i>. 2017;81C:46-55. doi:<a href=\"https://doi.org/10.1016/j.automatica.2017.03.030\">10.1016/j.automatica.2017.03.030</a>","chicago":"Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input Invariances.” <i>Automatica</i>. International Federation of Automatic Control, 2017. <a href=\"https://doi.org/10.1016/j.automatica.2017.03.030\">https://doi.org/10.1016/j.automatica.2017.03.030</a>."},"has_accepted_license":"1","status":"public","ec_funded":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"A nonlinear system possesses an invariance with respect to a set of transformations if its output dynamics remain invariant when transforming the input, and adjusting the initial condition accordingly. Most research has focused on invariances with respect to time-independent pointwise transformations like translational-invariance (u(t) -&gt; u(t) + p, p in R) or scale-invariance (u(t) -&gt; pu(t), p in R&gt;0). In this article, we introduce the concept of s0-invariances with respect to continuous input transformations exponentially growing/decaying over time. We show that s0-invariant systems not only encompass linear time-invariant (LTI) systems with transfer functions having an irreducible zero at s0 in R, but also that the input/output relationship of nonlinear s0-invariant systems possesses properties well known from their linear counterparts. Furthermore, we extend the concept of s0-invariances to second- and higher-order s0-invariances, corresponding to invariances with respect to transformations of the time-derivatives of the input, and encompassing LTI systems with zeros of multiplicity two or higher. Finally, we show that nth-order 0-invariant systems realize – under mild conditions – nth-order nonlinear differential operators: when excited by an input of a characteristic functional form, the system’s output converges to a constant value only depending on the nth (nonlinear) derivative of the input.","lang":"eng"}],"title":"Zeros of nonlinear systems with input invariances","_id":"1007","date_created":"2018-12-11T11:49:39Z","day":"01","publist_id":"6391","publication_status":"published","author":[{"full_name":"Lang, Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","first_name":"Moritz","last_name":"Lang"},{"last_name":"Sontag","full_name":"Sontag, Eduardo","first_name":"Eduardo"}],"pubrep_id":"813","page":"46 - 55","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"ddc":["000"],"language":[{"iso":"eng"}],"year":"2017","external_id":{"isi":["000403513900006"]},"oa_version":"Published Version","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"type":"journal_article","date_published":"2017-06-01T00:00:00Z","volume":"81C","month":"06","oa":1,"quality_controlled":"1","file":[{"access_level":"open_access","file_name":"IST-2017-813-v1+1_ZerosOfNonlinearSystems.pdf","date_updated":"2018-12-12T10:11:29Z","file_size":1401954,"content_type":"application/pdf","file_id":"4884","date_created":"2018-12-12T10:11:29Z","creator":"system","relation":"main_file"}],"article_processing_charge":"Yes (in subscription journal)","doi":"10.1016/j.automatica.2017.03.030","publisher":"International Federation of Automatic Control","date_updated":"2023-10-17T08:51:18Z","publication":"Automatica"},{"year":"2017","language":[{"iso":"eng"}],"department":[{"_id":"AnKi"},{"_id":"GaTk"}],"author":[{"full_name":"Zagórski, Marcin P","first_name":"Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","last_name":"Zagórski"},{"full_name":"Tabata, Yoji","first_name":"Yoji","last_name":"Tabata"},{"full_name":"Brandenberg, Nathalie","first_name":"Nathalie","last_name":"Brandenberg"},{"last_name":"Lutolf","first_name":"Matthias","full_name":"Lutolf, Matthias"},{"last_name":"Tkacik","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper"},{"first_name":"Tobias","full_name":"Bollenbach, Tobias","last_name":"Bollenbach"},{"last_name":"Briscoe","first_name":"James","full_name":"Briscoe, James"},{"full_name":"Kicheva, Anna","id":"3959A2A0-F248-11E8-B48F-1D18A9856A87","first_name":"Anna","orcid":"0000-0003-4509-4998","last_name":"Kicheva"}],"page":"1379 - 1383","date_created":"2018-12-11T11:49:20Z","day":"30","publist_id":"6474","publication_status":"published","article_processing_charge":"No","publisher":"American Association for the Advancement of Science","date_updated":"2023-09-26T15:38:05Z","doi":"10.1126/science.aam5887","publication":"Science","month":"06","oa":1,"quality_controlled":"1","date_published":"2017-06-30T00:00:00Z","type":"journal_article","project":[{"name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"},{"name":"Coordination of Patterning And Growth In the Spinal Cord","call_identifier":"H2020","grant_number":"680037","_id":"B6FC0238-B512-11E9-945C-1524E6697425"},{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"},{"name":"Developing High-Throughput Bioassays for Human Cancers in Zebrafish","call_identifier":"FP7","grant_number":"201439","_id":"2524F500-B435-11E9-9278-68D0E5697425"}],"volume":356,"oa_version":"Submitted Version","external_id":{"isi":["000404351500036"],"pmid":["28663499"]},"scopus_import":"1","isi":1,"issue":"6345","publication_identifier":{"issn":["00368075"]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"text":"Like many developing tissues, the vertebrate neural tube is patterned by antiparallel morphogen gradients. To understand how these inputs are interpreted, we measured morphogen signaling and target gene expression in mouse embryos and chick ex vivo assays. From these data, we derived and validated a characteristic decoding map that relates morphogen input to the positional identity of neural progenitors. Analysis of the observed responses indicates that the underlying interpretation strategy minimizes patterning errors in response to the joint input of noisy opposing gradients. We reverse-engineered a transcriptional network that provides a mechanistic basis for the observed cell fate decisions and accounts for the precision and dynamics of pattern formation. Together, our data link opposing gradient dynamics in a growing tissue to precise pattern formation.","lang":"eng"}],"title":"Decoding of position in the developing neural tube from antiparallel morphogen gradients","_id":"943","pmid":1,"status":"public","ec_funded":1,"citation":{"chicago":"Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf, Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” <i>Science</i>. American Association for the Advancement of Science, 2017. <a href=\"https://doi.org/10.1126/science.aam5887\">https://doi.org/10.1126/science.aam5887</a>.","ama":"Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing neural tube from antiparallel morphogen gradients. <i>Science</i>. 2017;356(6345):1379-1383. doi:<a href=\"https://doi.org/10.1126/science.aam5887\">10.1126/science.aam5887</a>","mla":"Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” <i>Science</i>, vol. 356, no. 6345, American Association for the Advancement of Science, 2017, pp. 1379–83, doi:<a href=\"https://doi.org/10.1126/science.aam5887\">10.1126/science.aam5887</a>.","short":"M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach, J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.","ieee":"M. P. Zagórski <i>et al.</i>, “Decoding of position in the developing neural tube from antiparallel morphogen gradients,” <i>Science</i>, vol. 356, no. 6345. American Association for the Advancement of Science, pp. 1379–1383, 2017.","ista":"Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 356(6345), 1379–1383.","apa":"Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach, T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from antiparallel morphogen gradients. <i>Science</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/science.aam5887\">https://doi.org/10.1126/science.aam5887</a>"},"intvolume":"       356","main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/"}]},{"main_file_link":[{"url":"https://arxiv.org/abs/1703.00219","open_access":"1"}],"citation":{"ieee":"D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost of cellular growth control,” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 96, no. 1. American Institute of Physics, 2017.","short":"D. De Martino, F. Capuani, A. De Martino,  Physical Review E Statistical Nonlinear and Soft Matter Physics  96 (2017).","apa":"De Martino, D., Capuani, F., &#38; De Martino, A. (2017). Quantifying the entropic cost of cellular growth control. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics. <a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">https://doi.org/10.1103/PhysRevE.96.010401</a>","ista":"De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401.","chicago":"De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics, 2017. <a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">https://doi.org/10.1103/PhysRevE.96.010401</a>.","mla":"De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth Control.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">10.1103/PhysRevE.96.010401</a>.","ama":"De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. 2017;96(1). doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">10.1103/PhysRevE.96.010401</a>"},"intvolume":"        96","ec_funded":1,"status":"public","abstract":[{"text":"Viewing the ways a living cell can organize its metabolism as the phase space of a physical system, regulation can be seen as the ability to reduce the entropy of that space by selecting specific cellular configurations that are, in some sense, optimal. Here we quantify the amount of regulation required to control a cell's growth rate by a maximum-entropy approach to the space of underlying metabolic phenotypes, where a configuration corresponds to a metabolic flux pattern as described by genome-scale models. We link the mean growth rate achieved by a population of cells to the minimal amount of metabolic regulation needed to achieve it through a phase diagram that highlights how growth suppression can be as costly (in regulatory terms) as growth enhancement. Moreover, we provide an interpretation of the inverse temperature β controlling maximum-entropy distributions based on the underlying growth dynamics. Specifically, we show that the asymptotic value of β for a cell population can be expected to depend on (i) the carrying capacity of the environment, (ii) the initial size of the colony, and (iii) the probability distribution from which the inoculum was sampled. Results obtained for E. coli and human cells are found to be remarkably consistent with empirical evidence.","lang":"eng"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"947","title":"Quantifying the entropic cost of cellular growth control","publication_identifier":{"issn":["24700045"]},"issue":"1","isi":1,"scopus_import":"1","oa_version":"Submitted Version","external_id":{"isi":["000405194200002"]},"volume":96,"project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"date_published":"2017-07-10T00:00:00Z","type":"journal_article","month":"07","article_number":"010401","quality_controlled":"1","oa":1,"article_processing_charge":"No","publication":" Physical Review E Statistical Nonlinear and Soft Matter Physics ","publisher":"American Institute of Physics","date_updated":"2023-09-22T10:03:50Z","doi":"10.1103/PhysRevE.96.010401","date_created":"2018-12-11T11:49:21Z","publist_id":"6470","publication_status":"published","day":"10","author":[{"first_name":"Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","full_name":"De Martino, Daniele","last_name":"De Martino","orcid":"0000-0002-5214-4706"},{"first_name":"Fabrizio","full_name":"Capuani, Fabrizio","last_name":"Capuani"},{"last_name":"De Martino","first_name":"Andrea","full_name":"De Martino, Andrea"}],"department":[{"_id":"GaTk"}],"language":[{"iso":"eng"}],"year":"2017"}]