[{"article_processing_charge":"No","has_accepted_license":"1","day":"10","scopus_import":"1","date_published":"2018-09-10T00:00:00Z","page":"1633 - 1643","article_type":"original","citation":{"ama":"Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2018;2(10):1633-1643. doi:10.1038/s41559-018-0651-y","ista":"Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2(10), 1633–1643.","ieee":"C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Evolutionary potential of transcription factors for gene regulatory rewiring,” Nature Ecology and Evolution, vol. 2, no. 10. Nature Publishing Group, pp. 1633–1643, 2018.","apa":"Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018). Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. Nature Publishing Group. https://doi.org/10.1038/s41559-018-0651-y","mla":"Igler, Claudia, et al. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Nature Ecology and Evolution, vol. 2, no. 10, Nature Publishing Group, 2018, pp. 1633–43, doi:10.1038/s41559-018-0651-y.","short":"C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, Nature Ecology and Evolution 2 (2018) 1633–1643.","chicago":"Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin C Guet. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Nature Ecology and Evolution. Nature Publishing Group, 2018. https://doi.org/10.1038/s41559-018-0651-y."},"publication":"Nature Ecology and Evolution","issue":"10","abstract":[{"lang":"eng","text":"Gene regulatory networks evolve through rewiring of individual components—that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor–DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor–DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution."}],"type":"journal_article","oa_version":"Submitted Version","file":[{"access_level":"open_access","file_name":"2018_NatureEcology_Igler.pdf","creator":"dernst","content_type":"application/pdf","file_size":1135973,"file_id":"7830","relation":"main_file","checksum":"383a2e2c944a856e2e821ec8e7bf71b6","date_created":"2020-05-14T11:28:52Z","date_updated":"2020-07-14T12:47:37Z"}],"intvolume":" 2","ddc":["570"],"title":"Evolutionary potential of transcription factors for gene regulatory rewiring","status":"public","_id":"67","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","month":"09","language":[{"iso":"eng"}],"doi":"10.1038/s41559-018-0651-y","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"},{"grant_number":"648440","_id":"2578D616-B435-11E9-9278-68D0E5697425","name":"Selective Barriers to Horizontal Gene Transfer","call_identifier":"H2020"},{"name":"Design principles underlying genetic switch architecture (DOC Fellowship)","grant_number":"24573","_id":"251EE76E-B435-11E9-9278-68D0E5697425"}],"isi":1,"quality_controlled":"1","oa":1,"external_id":{"isi":["000447947600021"]},"publist_id":"7987","ec_funded":1,"file_date_updated":"2020-07-14T12:47:37Z","volume":2,"date_created":"2018-12-11T11:44:27Z","date_updated":"2024-03-28T23:30:49Z","related_material":{"record":[{"id":"5585","status":"public","relation":"popular_science"},{"status":"public","relation":"dissertation_contains","id":"6371"}]},"author":[{"last_name":"Igler","first_name":"Claudia","id":"46613666-F248-11E8-B48F-1D18A9856A87","full_name":"Igler, Claudia"},{"id":"345D25EC-F248-11E8-B48F-1D18A9856A87","last_name":"Lagator","first_name":"Mato","full_name":"Lagator, Mato"},{"full_name":"Tkacik, Gasper","first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455"},{"full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","last_name":"Bollback","first_name":"Jonathan P"},{"full_name":"Guet, Calin C","last_name":"Guet","first_name":"Calin C","orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"}],"publisher":"Nature Publishing Group","department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"JoBo"}],"publication_status":"published","year":"2018"},{"project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"},{"grant_number":"648440","_id":"2578D616-B435-11E9-9278-68D0E5697425","name":"Selective Barriers to Horizontal Gene Transfer","call_identifier":"H2020"},{"name":"Design principles underlying genetic switch architecture (DOC Fellowship)","_id":"251EE76E-B435-11E9-9278-68D0E5697425","grant_number":"24573"}],"tmp":{"short":"CC0 (1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"citation":{"chicago":"Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin C Guet. “Data for the Paper Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:108.","short":"C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, (2018).","mla":"Igler, Claudia, et al. Data for the Paper Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:108.","ieee":"C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring.” Institute of Science and Technology Austria, 2018.","apa":"Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018). Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:108","ista":"Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring, Institute of Science and Technology Austria, 10.15479/AT:ISTA:108.","ama":"Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring. 2018. doi:10.15479/AT:ISTA:108"},"oa":1,"date_published":"2018-07-20T00:00:00Z","doi":"10.15479/AT:ISTA:108","month":"07","day":"20","article_processing_charge":"No","has_accepted_license":"1","status":"public","title":"Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring","ddc":["576"],"department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"Institute of Science and Technology Austria","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"5585","year":"2018","date_updated":"2024-03-28T23:30:49Z","date_created":"2018-12-12T12:31:40Z","file":[{"creator":"system","content_type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","file_size":16507,"access_level":"open_access","file_name":"IST-2018-108-v1+1_data_figures.xlsx","checksum":"1435781526c77413802adee0d4583cce","date_updated":"2020-07-14T12:47:07Z","date_created":"2018-12-12T13:02:45Z","file_id":"5611","relation":"main_file"}],"oa_version":"Published Version","author":[{"full_name":"Igler, Claudia","last_name":"Igler","first_name":"Claudia","id":"46613666-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Lagator, Mato","id":"345D25EC-F248-11E8-B48F-1D18A9856A87","last_name":"Lagator","first_name":"Mato"},{"full_name":"Tkacik, Gasper","last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","last_name":"Bollback","first_name":"Jonathan P"},{"full_name":"Guet, Calin C","first_name":"Calin C","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052"}],"related_material":{"record":[{"status":"public","relation":"research_paper","id":"67"},{"relation":"research_paper","status":"public","id":"6371"}]},"datarep_id":"108","type":"research_data","license":"https://creativecommons.org/publicdomain/zero/1.0/","abstract":[{"text":"Mean repression values and standard error of the mean are given for all operator mutant libraries.","lang":"eng"}],"file_date_updated":"2020-07-14T12:47:07Z","ec_funded":1},{"intvolume":" 8","ddc":["576","579"],"title":"Shaping bacterial population behavior through computer interfaced control of individual cells","status":"public","_id":"613","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","file":[{"file_name":"IST-2017-911-v1+1_s41467-017-01683-1.pdf","access_level":"open_access","creator":"system","file_size":1951699,"content_type":"application/pdf","file_id":"5190","relation":"main_file","date_created":"2018-12-12T10:16:05Z","date_updated":"2020-07-14T12:47:20Z","checksum":"44bb5d0229926c23a9955d9fe0f9723f"}],"oa_version":"Published Version","pubrep_id":"911","type":"journal_article","issue":"1","abstract":[{"lang":"eng","text":"Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior."}],"citation":{"ieee":"R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping bacterial population behavior through computer interfaced control of individual cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.","apa":"Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., & Guet, C. C. (2017). Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-01683-1","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.","ama":"Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-01683-1","chicago":"Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-01683-1.","short":"R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications 8 (2017).","mla":"Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications, vol. 8, no. 1, 1535, Nature Publishing Group, 2017, doi:10.1038/s41467-017-01683-1."},"publication":"Nature Communications","date_published":"2017-12-01T00:00:00Z","scopus_import":1,"article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","day":"01","publisher":"Nature Publishing Group","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","year":"2017","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).","volume":8,"date_created":"2018-12-11T11:47:30Z","date_updated":"2021-01-12T08:06:15Z","author":[{"orcid":"0000-0003-0876-3187","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","last_name":"Chait","first_name":"Remy P","full_name":"Chait, Remy P"},{"full_name":"Ruess, Jakob","orcid":"0000-0003-1615-3282","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","last_name":"Ruess","first_name":"Jakob"},{"full_name":"Bergmiller, Tobias","first_name":"Tobias","last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","first_name":"Calin C","last_name":"Guet","full_name":"Guet, Calin C"}],"article_number":"1535","ec_funded":1,"publist_id":"7191","file_date_updated":"2020-07-14T12:47:20Z","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","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"}],"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"language":[{"iso":"eng"}],"doi":"10.1038/s41467-017-01683-1","publication_identifier":{"issn":["20411723"]},"month":"12"},{"date_updated":"2021-01-12T08:07:51Z","date_created":"2018-12-11T11:47:43Z","oa_version":"None","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"}],"status":"public","title":"Dynamical self consistency leads to behavioral development and emergent social interactions in robots","publication_status":"published","publisher":"IEEE","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"652","year":"2017","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"}],"publist_id":"7100","article_number":"7846789","type":"conference","language":[{"iso":"eng"}],"conference":{"name":"ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics ","start_date":"2016-09-19","location":"Cergy-Pontoise, France","end_date":"2016-09-22"},"date_published":"2017-02-07T00:00:00Z","doi":"10.1109/DEVLRN.2016.7846789","quality_controlled":"1","citation":{"chicago":"Der, Ralf, and Georg S Martius. “Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots.” IEEE, 2017. https://doi.org/10.1109/DEVLRN.2016.7846789.","mla":"Der, Ralf, and Georg S. Martius. Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots. 7846789, IEEE, 2017, doi:10.1109/DEVLRN.2016.7846789.","short":"R. Der, G.S. Martius, in:, IEEE, 2017.","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.","apa":"Der, R., & Martius, G. S. (2017). Dynamical self consistency leads to behavioral development and emergent social interactions in robots. Presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789","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.","ama":"Der R, Martius GS. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. In: IEEE; 2017. doi:10.1109/DEVLRN.2016.7846789"},"day":"07","month":"02","publication_identifier":{"isbn":["978-150905069-7"]},"scopus_import":1},{"doi":"10.3389/fnbot.2017.00008","language":[{"iso":"eng"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"}],"quality_controlled":"1","publication_identifier":{"issn":["16625218"]},"month":"03","author":[{"full_name":"Der, Ralf","first_name":"Ralf","last_name":"Der"},{"id":"3A276B68-F248-11E8-B48F-1D18A9856A87","last_name":"Martius","first_name":"Georg S","full_name":"Martius, Georg S"}],"volume":11,"date_updated":"2021-01-12T08:08:04Z","date_created":"2018-12-11T11:47:45Z","year":"2017","publisher":"Frontiers Research Foundation","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"publication_status":"published","publist_id":"7078","ec_funded":1,"file_date_updated":"2020-07-14T12:47:33Z","article_number":"00008","date_published":"2017-03-16T00:00:00Z","citation":{"chicago":"Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” Frontiers in Neurorobotics. Frontiers Research Foundation, 2017. https://doi.org/10.3389/fnbot.2017.00008.","short":"R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017).","mla":"Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” Frontiers in Neurorobotics, vol. 11, no. MAR, 00008, Frontiers Research Foundation, 2017, doi:10.3389/fnbot.2017.00008.","ieee":"R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal robots,” Frontiers in Neurorobotics, vol. 11, no. MAR. Frontiers Research Foundation, 2017.","apa":"Der, R., & Martius, G. S. (2017). Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research Foundation. https://doi.org/10.3389/fnbot.2017.00008","ista":"Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 11(MAR), 00008.","ama":"Der R, Martius GS. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 2017;11(MAR). doi:10.3389/fnbot.2017.00008"},"publication":"Frontiers in Neurorobotics","has_accepted_license":"1","article_processing_charge":"Yes","day":"16","scopus_import":1,"pubrep_id":"903","file":[{"file_size":8439566,"content_type":"application/pdf","creator":"system","access_level":"open_access","file_name":"IST-2017-903-v1+1_fnbot-11-00008.pdf","checksum":"b1bc43f96d1df3313c03032c2a46388d","date_created":"2018-12-12T10:18:49Z","date_updated":"2020-07-14T12:47:33Z","relation":"main_file","file_id":"5371"}],"oa_version":"Published Version","user_id":"2EBD1598-F248-11E8-B48F-1D18A9856A87","_id":"658","intvolume":" 11","ddc":["006"],"status":"public","title":"Self organized behavior generation for musculoskeletal robots","issue":"MAR","abstract":[{"lang":"eng","text":"With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics."}],"type":"journal_article"},{"language":[{"iso":"eng"}],"doi":"10.1371/journal.pcbi.1005763","project":[{"grant_number":"RGP0065/2012","_id":"255008E4-B435-11E9-9278-68D0E5697425","name":"Information processing and computation in fish groups"},{"name":"Sensitivity to higher-order statistics in natural scenes","call_identifier":"FWF","_id":"254D1A94-B435-11E9-9278-68D0E5697425","grant_number":"P 25651-N26"}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"publication_identifier":{"issn":["1553734X"]},"month":"09","volume":13,"date_updated":"2021-01-12T08:12:21Z","date_created":"2018-12-11T11:48:08Z","author":[{"full_name":"Humplik, Jan","id":"2E9627A8-F248-11E8-B48F-1D18A9856A87","first_name":"Jan","last_name":"Humplik"},{"first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper"}],"department":[{"_id":"GaTk"}],"publisher":"Public Library of Science","publication_status":"published","year":"2017","publist_id":"6960","file_date_updated":"2020-07-14T12:47:53Z","article_number":"e1005763","date_published":"2017-09-19T00:00:00Z","citation":{"mla":"Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” PLoS Computational Biology, vol. 13, no. 9, e1005763, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005763.","short":"J. Humplik, G. Tkačik, PLoS Computational Biology 13 (2017).","chicago":"Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” PLoS Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005763.","ama":"Humplik J, Tkačik G. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 2017;13(9). doi:10.1371/journal.pcbi.1005763","ista":"Humplik J, Tkačik G. 2017. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 13(9), e1005763.","ieee":"J. Humplik and G. Tkačik, “Probabilistic models for neural populations that naturally capture global coupling and criticality,” PLoS Computational Biology, vol. 13, no. 9. Public Library of Science, 2017.","apa":"Humplik, J., & Tkačik, G. (2017). Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005763"},"publication":"PLoS Computational Biology","has_accepted_license":"1","article_processing_charge":"Yes","day":"19","scopus_import":1,"oa_version":"Published Version","file":[{"file_name":"IST-2017-884-v1+1_journal.pcbi.1005763.pdf","access_level":"open_access","content_type":"application/pdf","file_size":14167050,"creator":"system","relation":"main_file","file_id":"5352","date_created":"2018-12-12T10:18:30Z","date_updated":"2020-07-14T12:47:53Z","checksum":"81107096c19771c36ddbe6f0282a3acb"}],"pubrep_id":"884","intvolume":" 13","title":"Probabilistic models for neural populations that naturally capture global coupling and criticality","status":"public","ddc":["530","571"],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"720","issue":"9","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."}],"type":"journal_article"},{"publication_identifier":{"issn":["00278424"]},"month":"09","oa":1,"main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617265/","open_access":"1"}],"external_id":{"pmid":["28874581"]},"quality_controlled":"1","doi":"10.1073/pnas.1703817114","language":[{"iso":"eng"}],"publist_id":"6953","pmid":1,"year":"2017","publisher":"National Academy of Sciences","department":[{"_id":"GaTk"}],"publication_status":"published","author":[{"first_name":"Roy","last_name":"Harpaz","full_name":"Harpaz, Roy"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik","full_name":"Tkacik, Gasper"},{"last_name":"Schneidman","first_name":"Elad","full_name":"Schneidman, Elad"}],"volume":114,"date_created":"2018-12-11T11:48:10Z","date_updated":"2021-01-12T08:12:36Z","scopus_import":1,"day":"19","citation":{"chicago":"Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1703817114.","mla":"Harpaz, Roy, et al. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS, vol. 114, no. 38, National Academy of Sciences, 2017, pp. 10149–54, doi:10.1073/pnas.1703817114.","short":"R. Harpaz, G. Tkačik, E. Schneidman, PNAS 114 (2017) 10149–10154.","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.","apa":"Harpaz, R., Tkačik, G., & Schneidman, E. (2017). Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1703817114","ieee":"R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information processing predict individual behavior of fish in a group,” PNAS, vol. 114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017.","ama":"Harpaz R, Tkačik G, Schneidman E. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 2017;114(38):10149-10154. doi:10.1073/pnas.1703817114"},"publication":"PNAS","page":"10149 - 10154","date_published":"2017-09-19T00:00:00Z","type":"journal_article","issue":"38","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."}],"_id":"725","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 114","status":"public","title":"Discrete modes of social information processing predict individual behavior of fish in a group","oa_version":"Submitted Version"},{"main_file_link":[{"url":"https://doi.org/10.5061/dryad.1f1rc","open_access":"1"}],"citation":{"chicago":"Prentice, Jason, Olivier Marre, Mark Ioffe, Adrianna Loback, Gašper Tkačik, and Michael Berry. “Data from: Error-Robust Modes of the Retinal Population Code.” Dryad, 2017. https://doi.org/10.5061/dryad.1f1rc.","short":"J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, M. Berry, (2017).","mla":"Prentice, Jason, et al. Data from: Error-Robust Modes of the Retinal Population Code. Dryad, 2017, doi:10.5061/dryad.1f1rc.","apa":"Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M. (2017). Data from: Error-robust modes of the retinal population code. Dryad. https://doi.org/10.5061/dryad.1f1rc","ieee":"J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, and M. Berry, “Data from: Error-robust modes of the retinal population code.” Dryad, 2017.","ista":"Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. 2017. Data from: Error-robust modes of the retinal population code, Dryad, 10.5061/dryad.1f1rc.","ama":"Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. Data from: Error-robust modes of the retinal population code. 2017. doi:10.5061/dryad.1f1rc"},"oa":1,"date_published":"2017-10-18T00:00:00Z","doi":"10.5061/dryad.1f1rc","article_processing_charge":"No","day":"18","month":"10","department":[{"_id":"GaTk"}],"publisher":"Dryad","title":"Data from: Error-robust modes of the retinal population code","status":"public","_id":"9709","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","year":"2017","oa_version":"Published Version","date_created":"2021-07-23T11:34:34Z","date_updated":"2023-02-21T16:34:41Z","related_material":{"record":[{"id":"1197","relation":"used_in_publication","status":"public"}]},"author":[{"full_name":"Prentice, Jason","last_name":"Prentice","first_name":"Jason"},{"full_name":"Marre, Olivier","first_name":"Olivier","last_name":"Marre"},{"full_name":"Ioffe, Mark","first_name":"Mark","last_name":"Ioffe"},{"last_name":"Loback","first_name":"Adrianna","full_name":"Loback, Adrianna"},{"last_name":"Tkačik","first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper"},{"full_name":"Berry, Michael","last_name":"Berry","first_name":"Michael"}],"type":"research_data_reference","abstract":[{"text":"Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells’ collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina.","lang":"eng"}]},{"citation":{"chicago":"Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582.","short":"M.J. Chalk, P. Masset, B. Gutkin, S. Denève, PLoS Computational Biology 13 (2017).","mla":"Chalk, Matthew J., et al. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational Biology, vol. 13, no. 6, e1005582, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005582.","ieee":"M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts divisive reshaping of receptive fields,” PLoS Computational Biology, vol. 13, no. 6. Public Library of Science, 2017.","apa":"Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582","ista":"Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 13(6), e1005582.","ama":"Chalk MJ, Masset P, Gutkin B, Denève S. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 2017;13(6). doi:10.1371/journal.pcbi.1005582"},"publication":"PLoS Computational Biology","date_published":"2017-06-01T00:00:00Z","scopus_import":1,"has_accepted_license":"1","day":"01","intvolume":" 13","title":"Sensory noise predicts divisive reshaping of receptive fields","status":"public","ddc":["571"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"680","file":[{"file_id":"4645","relation":"main_file","date_updated":"2020-07-14T12:47:40Z","date_created":"2018-12-12T10:07:47Z","checksum":"796a1026076af6f4405a47d985bc7b68","file_name":"IST-2017-898-v1+1_journal.pcbi.1005582.pdf","access_level":"open_access","creator":"system","content_type":"application/pdf","file_size":14555676}],"oa_version":"Published Version","pubrep_id":"898","type":"journal_article","issue":"6","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"}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"language":[{"iso":"eng"}],"doi":"10.1371/journal.pcbi.1005582","publication_identifier":{"issn":["1553734X"]},"month":"06","department":[{"_id":"GaTk"}],"publisher":"Public Library of Science","publication_status":"published","year":"2017","volume":13,"date_created":"2018-12-11T11:47:53Z","date_updated":"2023-02-23T14:10:54Z","related_material":{"record":[{"id":"9855","relation":"research_data","status":"public"}]},"author":[{"full_name":"Chalk, Matthew J","id":"2BAAC544-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7782-4436","first_name":"Matthew J","last_name":"Chalk"},{"full_name":"Masset, Paul","last_name":"Masset","first_name":"Paul"},{"full_name":"Gutkin, Boris","first_name":"Boris","last_name":"Gutkin"},{"first_name":"Sophie","last_name":"Denève","full_name":"Denève, Sophie"}],"article_number":"e1005582","publist_id":"7035","file_date_updated":"2020-07-14T12:47:40Z"},{"citation":{"ista":"Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Supplementary appendix, Public Library of Science, 10.1371/journal.pcbi.1005582.s001.","ieee":"M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Supplementary appendix.” Public Library of Science, 2017.","apa":"Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Supplementary appendix. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582.s001","ama":"Chalk MJ, Masset P, Gutkin B, Denève S. Supplementary appendix. 2017. doi:10.1371/journal.pcbi.1005582.s001","chicago":"Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Supplementary Appendix.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582.s001.","mla":"Chalk, Matthew J., et al. Supplementary Appendix. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005582.s001.","short":"M.J. Chalk, P. Masset, B. Gutkin, S. Denève, (2017)."},"doi":"10.1371/journal.pcbi.1005582.s001","date_published":"2017-06-01T00:00:00Z","article_processing_charge":"No","day":"01","month":"06","publisher":"Public Library of Science","department":[{"_id":"GaTk"}],"status":"public","title":"Supplementary appendix","_id":"9855","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","year":"2017","oa_version":"Published Version","date_created":"2021-08-10T07:05:10Z","date_updated":"2023-02-23T12:52:17Z","related_material":{"record":[{"id":"680","status":"public","relation":"used_in_publication"}]},"author":[{"last_name":"Chalk","first_name":"Matthew J","orcid":"0000-0001-7782-4436","id":"2BAAC544-F248-11E8-B48F-1D18A9856A87","full_name":"Chalk, Matthew J"},{"first_name":"Paul","last_name":"Masset","full_name":"Masset, Paul"},{"first_name":"Boris","last_name":"Gutkin","full_name":"Gutkin, Boris"},{"full_name":"Denève, Sophie","first_name":"Sophie","last_name":"Denève"}],"type":"research_data_reference","abstract":[{"text":"Includes derivation of optimal estimation algorithm, generalisation to non-poisson noise statistics, correlated input noise, and implementation of in a multi-layer neural network.","lang":"eng"}]},{"related_material":{"record":[{"id":"818","relation":"dissertation_contains","status":"public"}]},"author":[{"full_name":"Mitosch, Karin","last_name":"Mitosch","first_name":"Karin","id":"39B66846-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Rieckh, Georg","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","last_name":"Rieckh"},{"first_name":"Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Tobias"}],"volume":4,"date_created":"2018-12-11T11:47:48Z","date_updated":"2023-09-07T12:00:25Z","year":"2017","publisher":"Cell Press","department":[{"_id":"ToBo"},{"_id":"GaTk"}],"publication_status":"published","publist_id":"7061","ec_funded":1,"file_date_updated":"2020-07-14T12:47:35Z","doi":"10.1016/j.cels.2017.03.001","language":[{"iso":"eng"}],"oa":1,"tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png"},"project":[{"grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Optimality principles in responses to antibiotics"},{"call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22"},{"name":"Revealing the fundamental limits of cell growth","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","grant_number":"RGP0042/2013"}],"quality_controlled":"1","publication_identifier":{"issn":["24054712"]},"month":"04","pubrep_id":"901","oa_version":"Published Version","file":[{"creator":"system","content_type":"application/pdf","file_size":2438660,"file_name":"IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf","access_level":"open_access","date_updated":"2020-07-14T12:47:35Z","date_created":"2018-12-12T10:13:54Z","checksum":"04ff20011c3d9a601c514aa999a5fe1a","file_id":"5041","relation":"main_file"}],"_id":"666","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","intvolume":" 4","title":"Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment","ddc":["576","610"],"status":"public","issue":"4","abstract":[{"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.","lang":"eng"}],"type":"journal_article","date_published":"2017-04-26T00:00:00Z","citation":{"mla":"Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no. 4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001.","short":"K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.","chicago":"Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems. Cell Press, 2017. https://doi.org/10.1016/j.cels.2017.03.001.","ama":"Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001","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., & Bollenbach, M. T. (2017). Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001","ieee":"K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment,” Cell Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017."},"publication":"Cell Systems","page":"393 - 403","article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","day":"26","scopus_import":1},{"type":"journal_article","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."}],"issue":"2","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"2016","title":"Exact goodness-of-fit testing for the Ising model","status":"public","intvolume":" 44","oa_version":"Preprint","scopus_import":"1","day":"01","article_processing_charge":"No","publication":"Scandinavian Journal of Statistics","citation":{"short":"A. Martin Del Campo Sanchez, S.A. Cepeda Humerez, C. Uhler, Scandinavian Journal of Statistics 44 (2017) 285–306.","mla":"Martin Del Campo Sanchez, Abraham, et al. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal of Statistics, vol. 44, no. 2, Wiley-Blackwell, 2017, pp. 285–306, doi:10.1111/sjos.12251.","chicago":"Martin Del Campo Sanchez, Abraham, Sarah A Cepeda Humerez, and Caroline Uhler. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal of Statistics. Wiley-Blackwell, 2017. https://doi.org/10.1111/sjos.12251.","ama":"Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 2017;44(2):285-306. doi:10.1111/sjos.12251","apa":"Martin Del Campo Sanchez, A., Cepeda Humerez, S. A., & Uhler, C. (2017). Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. Wiley-Blackwell. https://doi.org/10.1111/sjos.12251","ieee":"A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit testing for the Ising model,” Scandinavian Journal of Statistics, vol. 44, no. 2. Wiley-Blackwell, pp. 285–306, 2017.","ista":"Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. 2017. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 44(2), 285–306."},"page":"285 - 306","date_published":"2017-06-01T00:00:00Z","publist_id":"5060","year":"2017","publication_status":"published","publisher":"Wiley-Blackwell","department":[{"_id":"GaTk"}],"author":[{"full_name":"Martin Del Campo Sanchez, Abraham","first_name":"Abraham","last_name":"Martin Del Campo Sanchez"},{"full_name":"Cepeda Humerez, Sarah A","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","first_name":"Sarah A","last_name":"Cepeda Humerez"},{"full_name":"Uhler, Caroline","first_name":"Caroline","last_name":"Uhler","id":"49ADD78E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7008-0216"}],"related_material":{"record":[{"id":"6473","relation":"part_of_dissertation","status":"public"}]},"date_created":"2018-12-11T11:55:13Z","date_updated":"2023-09-19T15:13:27Z","volume":44,"month":"06","publication_identifier":{"issn":["03036898"]},"oa":1,"external_id":{"isi":["000400985000001"],"arxiv":["1410.1242"]},"main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1410.1242"}],"isi":1,"quality_controlled":"1","doi":"10.1111/sjos.12251","language":[{"iso":"eng"}]},{"publication":"Nature Communications","citation":{"chicago":"Deny, Stephane, Ulisse Ferrari, Emilie Mace, Pierre Yger, Romain Caplette, Serge Picaud, Gašper Tkačik, and Olivier Marre. “Multiplexed Computations in Retinal Ganglion Cells of a Single Type.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-02159-y.","mla":"Deny, Stephane, et al. “Multiplexed Computations in Retinal Ganglion Cells of a Single Type.” Nature Communications, vol. 8, no. 1, 1964, Nature Publishing Group, 2017, doi:10.1038/s41467-017-02159-y.","short":"S. Deny, U. Ferrari, E. Mace, P. Yger, R. Caplette, S. Picaud, G. Tkačik, O. Marre, Nature Communications 8 (2017).","ista":"Deny S, Ferrari U, Mace E, Yger P, Caplette R, Picaud S, Tkačik G, Marre O. 2017. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 8(1), 1964.","apa":"Deny, S., Ferrari, U., Mace, E., Yger, P., Caplette, R., Picaud, S., … Marre, O. (2017). Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-02159-y","ieee":"S. Deny et al., “Multiplexed computations in retinal ganglion cells of a single type,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.","ama":"Deny S, Ferrari U, Mace E, et al. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-02159-y"},"date_published":"2017-12-06T00:00:00Z","scopus_import":"1","day":"06","has_accepted_license":"1","article_processing_charge":"No","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"1104","status":"public","ddc":["571"],"title":"Multiplexed computations in retinal ganglion cells of a single type","intvolume":" 8","pubrep_id":"921","file":[{"date_updated":"2018-12-12T10:16:06Z","date_created":"2018-12-12T10:16:06Z","relation":"main_file","file_id":"5191","file_size":2872887,"content_type":"application/pdf","creator":"system","file_name":"IST-2018-921-v1+1_s41467-017-02159-y.pdf","access_level":"open_access"}],"oa_version":"Published Version","type":"journal_article","abstract":[{"lang":"eng","text":"In the early visual system, cells of the same type perform the same computation in different places of the visual field. How these cells code together a complex visual scene is unclear. A common assumption is that cells of a single-type extract a single-stimulus feature to form a feature map, but this has rarely been observed directly. Using large-scale recordings in the rat retina, we show that a homogeneous population of fast OFF ganglion cells simultaneously encodes two radically different features of a visual scene. Cells close to a moving object code quasilinearly for its position, while distant cells remain largely invariant to the object's position and, instead, respond nonlinearly to changes in the object's speed. We develop a quantitative model that accounts for this effect and identify a disinhibitory circuit that mediates it. Ganglion cells of a single type thus do not code for one, but two features simultaneously. This richer, flexible neural map might also be present in other sensory systems."}],"issue":"1","external_id":{"isi":["000417241200004"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"quality_controlled":"1","isi":1,"project":[{"_id":"25CD3DD2-B435-11E9-9278-68D0E5697425","grant_number":"604102","name":"Localization of ion channels and receptors by two and three-dimensional immunoelectron microscopic approaches","call_identifier":"FP7"},{"call_identifier":"FWF","name":"Sensitivity to higher-order statistics in natural scenes","_id":"254D1A94-B435-11E9-9278-68D0E5697425","grant_number":"P 25651-N26"}],"doi":"10.1038/s41467-017-02159-y","language":[{"iso":"eng"}],"month":"12","publication_identifier":{"issn":["20411723"]},"year":"2017","publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Nature Publishing Group","author":[{"first_name":"Stephane","last_name":"Deny","full_name":"Deny, Stephane"},{"full_name":"Ferrari, Ulisse","first_name":"Ulisse","last_name":"Ferrari"},{"full_name":"Mace, Emilie","first_name":"Emilie","last_name":"Mace"},{"full_name":"Yger, Pierre","last_name":"Yger","first_name":"Pierre"},{"last_name":"Caplette","first_name":"Romain","full_name":"Caplette, Romain"},{"last_name":"Picaud","first_name":"Serge","full_name":"Picaud, Serge"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik"},{"full_name":"Marre, Olivier","first_name":"Olivier","last_name":"Marre"}],"date_created":"2018-12-11T11:50:10Z","date_updated":"2023-09-20T11:41:19Z","volume":8,"article_number":"1964","file_date_updated":"2018-12-12T10:16:06Z","ec_funded":1,"publist_id":"6266"},{"scopus_import":"1","has_accepted_license":"1","article_processing_charge":"Yes (in subscription journal)","day":"04","citation":{"chicago":"Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/ncomms15140.","mla":"Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature Communications, vol. 8, 15140, Nature Publishing Group, 2017, doi:10.1038/ncomms15140.","short":"A. Levina (Martius), V. Priesemann, Nature Communications 8 (2017).","ista":"Levina (Martius) A, Priesemann V. 2017. Subsampling scaling. Nature Communications. 8, 15140.","apa":"Levina (Martius), A., & Priesemann, V. (2017). Subsampling scaling. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms15140","ieee":"A. Levina (Martius) and V. Priesemann, “Subsampling scaling,” Nature Communications, vol. 8. Nature Publishing Group, 2017.","ama":"Levina (Martius) A, Priesemann V. Subsampling scaling. Nature Communications. 2017;8. doi:10.1038/ncomms15140"},"publication":"Nature Communications","date_published":"2017-05-04T00:00:00Z","type":"journal_article","abstract":[{"lang":"eng","text":"In real-world applications, observations are often constrained to a small fraction of a system. Such spatial subsampling can be caused by the inaccessibility or the sheer size of the system, and cannot be overcome by longer sampling. Spatial subsampling can strongly bias inferences about a system’s aggregated properties. To overcome the bias, we derive analytically a subsampling scaling framework that is applicable to different observables, including distributions of neuronal avalanches, of number of people infected during an epidemic outbreak, and of node degrees. We demonstrate how to infer the correct distributions of the underlying full system, how to apply it to distinguish critical from subcritical systems, and how to disentangle subsampling and finite size effects. Lastly, we apply subsampling scaling to neuronal avalanche models and to recordings from developing neural networks. We show that only mature, but not young networks follow power-law scaling, indicating self-organization to criticality during development."}],"intvolume":" 8","title":"Subsampling scaling","status":"public","ddc":["005","571"],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"993","file":[{"creator":"system","file_size":746224,"content_type":"application/pdf","file_name":"IST-2017-819-v1+1_2017_Levina_SubsamplingScaling.pdf","access_level":"open_access","date_updated":"2020-07-14T12:48:19Z","date_created":"2018-12-12T10:15:05Z","checksum":"9880212f8c4c53404c7c6fbf9023c53a","file_id":"5122","relation":"main_file"}],"oa_version":"Published Version","pubrep_id":"819","publication_identifier":{"issn":["20411723"]},"month":"05","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"}],"quality_controlled":"1","isi":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"external_id":{"isi":["000400560700001"]},"language":[{"iso":"eng"}],"doi":"10.1038/ncomms15140","article_number":"15140","ec_funded":1,"publist_id":"6406","file_date_updated":"2020-07-14T12:48:19Z","publisher":"Nature Publishing Group","department":[{"_id":"GaTk"},{"_id":"JoCs"}],"publication_status":"published","year":"2017","volume":8,"date_created":"2018-12-11T11:49:35Z","date_updated":"2023-09-22T09:54:07Z","author":[{"id":"35AF8020-F248-11E8-B48F-1D18A9856A87","last_name":"Levina (Martius)","first_name":"Anna","full_name":"Levina (Martius), Anna"},{"last_name":"Priesemann","first_name":"Viola","full_name":"Priesemann, Viola"}]},{"issue":"1","abstract":[{"lang":"eng","text":"Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components."}],"type":"journal_article","file":[{"file_id":"5064","relation":"main_file","checksum":"29a1b5db458048d3bd5c67e0e2a56818","date_updated":"2020-07-14T12:48:16Z","date_created":"2018-12-12T10:14:14Z","access_level":"open_access","file_name":"IST-2017-864-v1+1_s41467-017-00238-8.pdf","creator":"system","file_size":998157,"content_type":"application/pdf"},{"relation":"main_file","file_id":"5065","date_created":"2018-12-12T10:14:15Z","date_updated":"2020-07-14T12:48:16Z","checksum":"7b78401e52a576cf3e6bbf8d0abadc17","file_name":"IST-2017-864-v1+2_41467_2017_238_MOESM1_ESM.pdf","access_level":"open_access","content_type":"application/pdf","file_size":9715993,"creator":"system"}],"oa_version":"Published Version","pubrep_id":"864","intvolume":" 8","title":"Evolution of new regulatory functions on biophysically realistic fitness landscapes","status":"public","ddc":["539","576"],"_id":"955","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","day":"09","scopus_import":"1","date_published":"2017-08-09T00:00:00Z","citation":{"chicago":"Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-00238-8.","mla":"Friedlander, Tamar, et al. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications, vol. 8, no. 1, 216, Nature Publishing Group, 2017, doi:10.1038/s41467-017-00238-8.","short":"T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications 8 (2017).","ista":"Friedlander T, Prizak R, Barton NH, Tkačik G. 2017. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 8(1), 216.","apa":"Friedlander, T., Prizak, R., Barton, N. H., & Tkačik, G. (2017). Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-00238-8","ieee":"T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new regulatory functions on biophysically realistic fitness landscapes,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.","ama":"Friedlander T, Prizak R, Barton NH, Tkačik G. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-00238-8"},"publication":"Nature Communications","publist_id":"6459","ec_funded":1,"file_date_updated":"2020-07-14T12:48:16Z","article_number":"216","volume":8,"date_created":"2018-12-11T11:49:23Z","date_updated":"2023-09-22T10:00:49Z","related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"6071"}]},"author":[{"last_name":"Friedlander","first_name":"Tamar","id":"36A5845C-F248-11E8-B48F-1D18A9856A87","full_name":"Friedlander, Tamar"},{"first_name":"Roshan","last_name":"Prizak","id":"4456104E-F248-11E8-B48F-1D18A9856A87","full_name":"Prizak, Roshan"},{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik","full_name":"Tkacik, Gasper"}],"department":[{"_id":"GaTk"},{"_id":"NiBa"}],"publisher":"Nature Publishing Group","publication_status":"published","year":"2017","publication_identifier":{"issn":["20411723"]},"month":"08","language":[{"iso":"eng"}],"doi":"10.1038/s41467-017-00238-8","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"},{"_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7"},{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation"}],"quality_controlled":"1","isi":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"external_id":{"isi":["000407198800005"]}},{"publist_id":"6446","ec_funded":1,"author":[{"first_name":"Daniele","last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","full_name":"De Martino, Daniele"}],"volume":95,"date_created":"2018-12-11T11:49:25Z","date_updated":"2023-09-22T09:59:01Z","year":"2017","publisher":"American Institute of Physics","department":[{"_id":"GaTk"}],"publication_status":"published","publication_identifier":{"issn":["24700045"]},"month":"06","doi":"10.1103/PhysRevE.95.062419","language":[{"iso":"eng"}],"external_id":{"isi":["000404546400004"]},"oa":1,"main_file_link":[{"url":"https://arxiv.org/pdf/1703.00853.pdf","open_access":"1"}],"project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","isi":1,"issue":"6","abstract":[{"text":"In this work it is shown that scale-free tails in metabolic flux distributions inferred in stationary models are an artifact due to reactions involved in thermodynamically unfeasible cycles, unbounded by physical constraints and in principle able to perform work without expenditure of free energy. After implementing thermodynamic constraints by removing such loops, metabolic flux distributions scale meaningfully with the physical limiting factors, acquiring in turn a richer multimodal structure potentially leading to symmetry breaking while optimizing for objective functions.","lang":"eng"}],"type":"journal_article","oa_version":"Submitted Version","_id":"959","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","intvolume":" 95","status":"public","title":"Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics","article_processing_charge":"No","day":"28","scopus_import":"1","date_published":"2017-06-28T00:00:00Z","citation":{"short":"D. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 95 (2017) 062419.","mla":"De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 95, no. 6, American Institute of Physics, 2017, p. 062419, doi:10.1103/PhysRevE.95.062419.","chicago":"De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.95.062419.","ama":"De Martino D. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;95(6):062419. doi:10.1103/PhysRevE.95.062419","ieee":"D. De Martino, “Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics,” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 95, no. 6. American Institute of Physics, p. 062419, 2017.","apa":"De Martino, D. (2017). Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.95.062419","ista":"De Martino D. 2017. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 95(6), 062419."},"publication":" Physical Review E Statistical Nonlinear and Soft Matter Physics ","page":"062419"},{"issue":"1","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"}],"type":"journal_article","oa_version":"Submitted Version","intvolume":" 96","status":"public","title":"Quantifying the entropic cost of cellular growth control","_id":"947","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","article_processing_charge":"No","day":"10","scopus_import":"1","date_published":"2017-07-10T00:00:00Z","citation":{"chicago":"De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401.","short":"D. De Martino, F. Capuani, A. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 96 (2017).","mla":"De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:10.1103/PhysRevE.96.010401.","apa":"De Martino, D., Capuani, F., & De Martino, A. (2017). Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401","ieee":"D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost of cellular growth control,” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1. American Institute of Physics, 2017.","ista":"De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401.","ama":"De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;96(1). doi:10.1103/PhysRevE.96.010401"},"publication":" Physical Review E Statistical Nonlinear and Soft Matter Physics ","ec_funded":1,"publist_id":"6470","article_number":"010401","volume":96,"date_created":"2018-12-11T11:49:21Z","date_updated":"2023-09-22T10:03:50Z","author":[{"id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","first_name":"Daniele","last_name":"De Martino","full_name":"De Martino, Daniele"},{"first_name":"Fabrizio","last_name":"Capuani","full_name":"Capuani, Fabrizio"},{"full_name":"De Martino, Andrea","first_name":"Andrea","last_name":"De Martino"}],"publisher":"American Institute of Physics","department":[{"_id":"GaTk"}],"publication_status":"published","year":"2017","publication_identifier":{"issn":["24700045"]},"month":"07","language":[{"iso":"eng"}],"doi":"10.1103/PhysRevE.96.010401","project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","isi":1,"external_id":{"isi":["000405194200002"]},"main_file_link":[{"url":"https://arxiv.org/abs/1703.00219","open_access":"1"}],"oa":1},{"day":"30","article_processing_charge":"No","scopus_import":"1","date_published":"2017-06-30T00:00:00Z","page":"1379 - 1383","publication":"Science","citation":{"ama":"Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383. doi:10.1126/science.aam5887","ieee":"M. P. Zagórski et al., “Decoding of position in the developing neural tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345. American Association for the Advancement of Science, pp. 1379–1383, 2017.","apa":"Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach, T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aam5887","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.","short":"M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach, J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.","mla":"Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” Science, vol. 356, no. 6345, American Association for the Advancement of Science, 2017, pp. 1379–83, doi:10.1126/science.aam5887.","chicago":"Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf, Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aam5887."},"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"}],"issue":"6345","type":"journal_article","oa_version":"Submitted Version","status":"public","title":"Decoding of position in the developing neural tube from antiparallel morphogen gradients","intvolume":" 356","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"943","month":"06","publication_identifier":{"issn":["00368075"]},"language":[{"iso":"eng"}],"doi":"10.1126/science.aam5887","isi":1,"quality_controlled":"1","project":[{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"},{"name":"Coordination of Patterning And Growth In the Spinal Cord","call_identifier":"H2020","_id":"B6FC0238-B512-11E9-945C-1524E6697425","grant_number":"680037"},{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"},{"name":"Developing High-Throughput Bioassays for Human Cancers in Zebrafish","call_identifier":"FP7","_id":"2524F500-B435-11E9-9278-68D0E5697425","grant_number":"201439"}],"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/"}],"external_id":{"pmid":["28663499"],"isi":["000404351500036"]},"oa":1,"ec_funded":1,"publist_id":"6474","date_updated":"2023-09-26T15:38:05Z","date_created":"2018-12-11T11:49:20Z","volume":356,"author":[{"full_name":"Zagórski, Marcin P","first_name":"Marcin P","last_name":"Zagórski","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762"},{"last_name":"Tabata","first_name":"Yoji","full_name":"Tabata, Yoji"},{"full_name":"Brandenberg, Nathalie","last_name":"Brandenberg","first_name":"Nathalie"},{"last_name":"Lutolf","first_name":"Matthias","full_name":"Lutolf, Matthias"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik","full_name":"Tkacik, Gasper"},{"full_name":"Bollenbach, Tobias","first_name":"Tobias","last_name":"Bollenbach"},{"first_name":"James","last_name":"Briscoe","full_name":"Briscoe, James"},{"full_name":"Kicheva, Anna","first_name":"Anna","last_name":"Kicheva","id":"3959A2A0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4509-4998"}],"publication_status":"published","publisher":"American Association for the Advancement of Science","department":[{"_id":"AnKi"},{"_id":"GaTk"}],"year":"2017","pmid":1},{"article_number":"093404","publist_id":"6826","ec_funded":1,"department":[{"_id":"GaTk"}],"publisher":"IOPscience","publication_status":"published","year":"2017","volume":2017,"date_created":"2018-12-11T11:48:41Z","date_updated":"2023-09-26T16:18:12Z","author":[{"full_name":"Colabrese, Simona","last_name":"Colabrese","first_name":"Simona"},{"full_name":"De Martino, Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","first_name":"Daniele","last_name":"De Martino"},{"last_name":"Leuzzi","first_name":"Luca","full_name":"Leuzzi, Luca"},{"last_name":"Marinari","first_name":"Enzo","full_name":"Marinari, Enzo"}],"publication_identifier":{"issn":["17425468"]},"month":"09","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","isi":1,"oa":1,"external_id":{"isi":["000411842900001"]},"main_file_link":[{"url":"https://arxiv.org/abs/1705.06303","open_access":"1"}],"language":[{"iso":"eng"}],"doi":"10.1088/1742-5468/aa85c3","type":"journal_article","issue":"9","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"}],"intvolume":" 2017","title":"Phase transitions in integer linear problems","status":"public","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"823","oa_version":"Submitted Version","scopus_import":"1","article_processing_charge":"No","day":"26","citation":{"ama":"Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. 2017;2017(9). doi:10.1088/1742-5468/aa85c3","ieee":"S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions in integer linear problems,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9. IOPscience, 2017.","apa":"Colabrese, S., De Martino, D., Leuzzi, L., & Marinari, E. (2017). Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa85c3","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.","short":"S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari, Journal of Statistical Mechanics: Theory and Experiment 2017 (2017).","mla":"Colabrese, Simona, et al. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9, 093404, IOPscience, 2017, doi:10.1088/1742-5468/aa85c3.","chicago":"Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2017. https://doi.org/10.1088/1742-5468/aa85c3."},"publication":" Journal of Statistical Mechanics: Theory and Experiment","date_published":"2017-09-26T00:00:00Z"},{"page":"120 - 126","citation":{"ista":"Savin C, Tkačik G. 2017. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 46, 120–126.","apa":"Savin, C., & Tkačik, G. (2017). Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. Elsevier. https://doi.org/10.1016/j.conb.2017.08.001","ieee":"C. Savin and G. Tkačik, “Maximum entropy models as a tool for building precise neural controls,” Current Opinion in Neurobiology, vol. 46. Elsevier, pp. 120–126, 2017.","ama":"Savin C, Tkačik G. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 2017;46:120-126. doi:10.1016/j.conb.2017.08.001","chicago":"Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” Current Opinion in Neurobiology. Elsevier, 2017. https://doi.org/10.1016/j.conb.2017.08.001.","mla":"Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” Current Opinion in Neurobiology, vol. 46, Elsevier, 2017, pp. 120–26, doi:10.1016/j.conb.2017.08.001.","short":"C. Savin, G. Tkačik, Current Opinion in Neurobiology 46 (2017) 120–126."},"publication":"Current Opinion in Neurobiology","date_published":"2017-10-01T00:00:00Z","scopus_import":"1","article_processing_charge":"No","day":"01","intvolume":" 46","title":"Maximum entropy models as a tool for building precise neural controls","status":"public","_id":"730","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa_version":"None","type":"journal_article","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"}],"project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"}],"quality_controlled":"1","isi":1,"external_id":{"isi":["000416196400016"]},"language":[{"iso":"eng"}],"doi":"10.1016/j.conb.2017.08.001","publication_identifier":{"issn":["09594388"]},"month":"10","department":[{"_id":"GaTk"}],"publisher":"Elsevier","publication_status":"published","year":"2017","volume":46,"date_updated":"2023-09-28T11:32:22Z","date_created":"2018-12-11T11:48:11Z","author":[{"last_name":"Savin","first_name":"Cristina","id":"3933349E-F248-11E8-B48F-1D18A9856A87","full_name":"Savin, Cristina"},{"full_name":"Tkacik, Gasper","last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"}],"publist_id":"6943","ec_funded":1},{"publist_id":"7266","ec_funded":1,"article_number":"060401","author":[{"first_name":"Daniele","last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","full_name":"De Martino, Daniele"}],"date_updated":"2023-10-10T13:29:38Z","date_created":"2018-12-11T11:47:06Z","volume":96,"year":"2017","publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"American Physical Society","month":"12","publication_identifier":{"issn":["2470-0045"]},"doi":"10.1103/PhysRevE.96.060401","language":[{"iso":"eng"}],"oa":1,"main_file_link":[{"url":"https://arxiv.org/abs/1707.00320","open_access":"1"}],"quality_controlled":"1","project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"abstract":[{"lang":"eng","text":"In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region."}],"issue":"6","type":"journal_article","alternative_title":["Rapid Communications"],"oa_version":"Submitted Version","_id":"548","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","title":"Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes","intvolume":" 96","day":"21","article_processing_charge":"No","scopus_import":"1","date_published":"2017-12-21T00:00:00Z","publication":"Physical Review E","citation":{"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. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.96.060401","ieee":"D. De Martino, “Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes,” Physical Review E, vol. 96, no. 6. American Physical Society, 2017.","ama":"De Martino D. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 2017;96(6). doi:10.1103/PhysRevE.96.060401","chicago":"De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E. American Physical Society, 2017. https://doi.org/10.1103/PhysRevE.96.060401.","mla":"De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E, vol. 96, no. 6, 060401, American Physical Society, 2017, doi:10.1103/PhysRevE.96.060401.","short":"D. De Martino, Physical Review E 96 (2017)."}},{"oa_version":"Published Version","file":[{"relation":"main_file","file_id":"4884","date_created":"2018-12-12T10:11:29Z","date_updated":"2018-12-12T10:11:29Z","file_name":"IST-2017-813-v1+1_ZerosOfNonlinearSystems.pdf","access_level":"open_access","content_type":"application/pdf","file_size":1401954,"creator":"system"}],"pubrep_id":"813","status":"public","ddc":["000"],"title":"Zeros of nonlinear systems with input invariances","_id":"1007","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) -> u(t) + p, p in R) or scale-invariance (u(t) -> pu(t), p in R>0). In this article, we introduce the concept of s0-invariances with respect to continuous input transformations exponentially growing/decaying over time. We show that s0-invariant systems not only encompass linear time-invariant (LTI) systems with transfer functions having an irreducible zero at s0 in R, but also that the input/output relationship of nonlinear s0-invariant systems possesses properties well known from their linear counterparts. Furthermore, we extend the concept of s0-invariances to second- and higher-order s0-invariances, corresponding to invariances with respect to transformations of the time-derivatives of the input, and encompassing LTI systems with zeros of multiplicity two or higher. Finally, we show that nth-order 0-invariant systems realize – under mild conditions – nth-order nonlinear differential operators: when excited by an input of a characteristic functional form, the system’s output converges to a constant value only depending on the nth (nonlinear) derivative of the input.","lang":"eng"}],"type":"journal_article","date_published":"2017-06-01T00:00:00Z","page":"46 - 55","citation":{"chicago":"Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input Invariances.” Automatica. International Federation of Automatic Control, 2017. https://doi.org/10.1016/j.automatica.2017.03.030.","short":"M. Lang, E. Sontag, Automatica 81C (2017) 46–55.","mla":"Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input Invariances.” Automatica, vol. 81C, International Federation of Automatic Control, 2017, pp. 46–55, doi:10.1016/j.automatica.2017.03.030.","apa":"Lang, M., & Sontag, E. (2017). Zeros of nonlinear systems with input invariances. Automatica. International Federation of Automatic Control. https://doi.org/10.1016/j.automatica.2017.03.030","ieee":"M. Lang and E. Sontag, “Zeros of nonlinear systems with input invariances,” Automatica, vol. 81C. International Federation of Automatic Control, pp. 46–55, 2017.","ista":"Lang M, Sontag E. 2017. Zeros of nonlinear systems with input invariances. Automatica. 81C, 46–55.","ama":"Lang M, Sontag E. Zeros of nonlinear systems with input invariances. Automatica. 2017;81C:46-55. doi:10.1016/j.automatica.2017.03.030"},"publication":"Automatica","article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","day":"01","scopus_import":"1","volume":"81C","date_created":"2018-12-11T11:49:39Z","date_updated":"2023-10-17T08:51:18Z","author":[{"full_name":"Lang, Moritz","first_name":"Moritz","last_name":"Lang","id":"29E0800A-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Sontag, Eduardo","last_name":"Sontag","first_name":"Eduardo"}],"publisher":"International Federation of Automatic Control","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","year":"2017","ec_funded":1,"publist_id":"6391","file_date_updated":"2018-12-12T10:11:29Z","language":[{"iso":"eng"}],"doi":"10.1016/j.automatica.2017.03.030","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"isi":1,"quality_controlled":"1","external_id":{"isi":["000403513900006"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"publication_identifier":{"issn":["0005-1098"]},"month":"06"},{"file":[{"file_name":"IST-2017-61-v1+1_bint_fishmovie32_100.mat","access_level":"open_access","creator":"system","content_type":"application/octet-stream","file_size":1336936,"file_id":"5622","relation":"main_file","date_updated":"2020-07-14T12:47:03Z","date_created":"2018-12-12T13:03:04Z","checksum":"e620eff260646f57b479a69492c8b765"},{"access_level":"open_access","file_name":"IST-2017-61-v1+2_bint_fishmovie32_100.zip","content_type":"application/zip","file_size":1897543,"creator":"system","relation":"main_file","file_id":"5623","checksum":"de83f9b81ea0aae3cddfc3ed982e0759","date_created":"2018-12-12T13:03:05Z","date_updated":"2020-07-14T12:47:03Z"}],"oa_version":"Published Version","date_created":"2018-12-12T12:31:33Z","date_updated":"2024-02-21T13:46:14Z","related_material":{"record":[{"id":"2257","status":"public","relation":"research_paper"}]},"author":[{"full_name":"Marre, Olivier","first_name":"Olivier","last_name":"Marre"},{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","first_name":"Gasper","full_name":"Tkacik, Gasper"},{"full_name":"Amodei, Dario","first_name":"Dario","last_name":"Amodei"},{"full_name":"Schneidman, Elad","last_name":"Schneidman","first_name":"Elad"},{"last_name":"Bialek","first_name":"William","full_name":"Bialek, William"},{"full_name":"Berry, Michael","last_name":"Berry","first_name":"Michael"}],"department":[{"_id":"GaTk"}],"publisher":"Institute of Science and Technology Austria","title":"Multi-electrode array recording from salamander retinal ganglion cells","ddc":["570"],"status":"public","year":"2017","_id":"5562","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"This data was collected as part of the study [1]. It consists of preprocessed multi-electrode array recording from 160 salamander retinal ganglion cells responding to 297 repeats of a 19 s natural movie. The data is available in two formats: (1) a .mat file containing an array with dimensions “number of repeats” x “number of neurons” x “time in a repeat”; (2) a zipped .txt file containing the same data represented as an array with dimensions “number of neurons” x “number of samples”, where the number of samples is equal to the product of the number of repeats and timebins within a repeat. The time dimension is divided into 20 ms time windows, and the array is binary indicating whether a given cell elicited at least one spike in a given time window during a particular repeat. See the reference below for details regarding collection and preprocessing:\r\n\r\n[1] Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry MJ II. Searching for Collective Behavior in a Large Network of Sensory Neurons. PLoS Comput Biol. 2014;10(1):e1003408."}],"file_date_updated":"2020-07-14T12:47:03Z","type":"research_data","datarep_id":"61","doi":"10.15479/AT:ISTA:61","date_published":"2017-02-27T00:00:00Z","citation":{"ista":"Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. 2017. Multi-electrode array recording from salamander retinal ganglion cells, Institute of Science and Technology Austria, 10.15479/AT:ISTA:61.","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.","apa":"Marre, O., Tkačik, G., Amodei, D., Schneidman, E., Bialek, W., & Berry, M. (2017). Multi-electrode array recording from salamander retinal ganglion cells. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:61","ama":"Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. Multi-electrode array recording from salamander retinal ganglion cells. 2017. doi:10.15479/AT:ISTA:61","chicago":"Marre, Olivier, Gašper Tkačik, Dario Amodei, Elad Schneidman, William Bialek, and Michael Berry. “Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:61.","mla":"Marre, Olivier, et al. Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:61.","short":"O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, M. Berry, (2017)."},"tmp":{"short":"CC0 (1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"oa":1,"has_accepted_license":"1","article_processing_charge":"No","month":"02","day":"27","keyword":["multi-electrode recording","retinal ganglion cells"]},{"keyword":["single cell microscopy","mother machine microfluidic device","AcrAB-TolC pump","multi-drug efflux","Escherichia coli"],"month":"03","day":"10","article_processing_charge":"No","has_accepted_license":"1","tmp":{"short":"CC0 (1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"citation":{"ista":"Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik G, Guet CC. 2017. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity, Institute of Science and Technology Austria, 10.15479/AT:ISTA:53.","apa":"Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:53","ieee":"T. Bergmiller et al., “Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity.” Institute of Science and Technology Austria, 2017.","ama":"Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. 2017. doi:10.15479/AT:ISTA:53","chicago":"Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:53.","mla":"Bergmiller, Tobias, et al. Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:53.","short":"T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, (2017)."},"oa":1,"doi":"10.15479/AT:ISTA:53","date_published":"2017-03-10T00:00:00Z","datarep_id":"53","type":"research_data","abstract":[{"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.","lang":"eng"}],"file_date_updated":"2020-07-14T12:47:03Z","ddc":["571"],"title":"Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity","status":"public","department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"Bio"}],"publisher":"Institute of Science and Technology Austria","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"5560","year":"2017","date_created":"2018-12-12T12:31:32Z","date_updated":"2024-02-21T13:49:00Z","file":[{"file_id":"5603","relation":"main_file","checksum":"d77859af757ac8025c50c7b12b52eaf3","date_created":"2018-12-12T13:02:38Z","date_updated":"2020-07-14T12:47:03Z","access_level":"open_access","file_name":"IST-2017-53-v1+1_Data_MDE.zip","creator":"system","file_size":6773204,"content_type":"application/zip"}],"oa_version":"Published Version","author":[{"full_name":"Bergmiller, Tobias","orcid":"0000-0001-5396-4346","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","last_name":"Bergmiller","first_name":"Tobias"},{"last_name":"Andersson","first_name":"Anna M","orcid":"0000-0003-2912-6769","id":"2B8A40DA-F248-11E8-B48F-1D18A9856A87","full_name":"Andersson, Anna M"},{"first_name":"Kathrin","last_name":"Tomasek","id":"3AEC8556-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3768-877X","full_name":"Tomasek, Kathrin"},{"full_name":"Balleza, Enrique","first_name":"Enrique","last_name":"Balleza"},{"full_name":"Kiviet, Daniel","last_name":"Kiviet","first_name":"Daniel"},{"full_name":"Hauschild, Robert","orcid":"0000-0001-9843-3522","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","last_name":"Hauschild","first_name":"Robert"},{"first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper"},{"last_name":"Guet","first_name":"Calin C","orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C"}],"related_material":{"record":[{"relation":"research_paper","status":"public","id":"665"}]}},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"665","intvolume":" 356","title":"Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity","status":"public","oa_version":"None","type":"journal_article","issue":"6335","abstract":[{"lang":"eng","text":"The molecular mechanisms underlying phenotypic variation in isogenic bacterial populations remain poorly understood.We report that AcrAB-TolC, the main multidrug efflux pump of Escherichia coli, exhibits a strong partitioning bias for old cell poles by a segregation mechanism that is mediated by ternary AcrAB-TolC complex formation. Mother cells inheriting old poles are phenotypically distinct and display increased drug efflux activity relative to daughters. Consequently, we find systematic and long-lived growth differences between mother and daughter cells in the presence of subinhibitory drug concentrations. A simple model for biased partitioning predicts a population structure of long-lived and highly heterogeneous phenotypes. This straightforward mechanism of generating sustained growth rate differences at subinhibitory antibiotic concentrations has implications for understanding the emergence of multidrug resistance in bacteria."}],"citation":{"mla":"Bergmiller, Tobias, et al. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” Science, vol. 356, no. 6335, American Association for the Advancement of Science, 2017, pp. 311–15, doi:10.1126/science.aaf4762.","short":"T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, Science 356 (2017) 311–315.","chicago":"Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aaf4762.","ama":"Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. 2017;356(6335):311-315. doi:10.1126/science.aaf4762","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.","apa":"Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aaf4762","ieee":"T. Bergmiller et al., “Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity,” Science, vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315, 2017."},"publication":"Science","page":"311 - 315","article_type":"original","date_published":"2017-04-21T00:00:00Z","scopus_import":1,"article_processing_charge":"No","day":"21","year":"2017","department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"Bio"}],"publisher":"American Association for the Advancement of Science","publication_status":"published","related_material":{"record":[{"relation":"popular_science","status":"public","id":"5560"}]},"author":[{"full_name":"Bergmiller, Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346","first_name":"Tobias","last_name":"Bergmiller"},{"full_name":"Andersson, Anna M","orcid":"0000-0003-2912-6769","id":"2B8A40DA-F248-11E8-B48F-1D18A9856A87","last_name":"Andersson","first_name":"Anna M"},{"full_name":"Tomasek, Kathrin","orcid":"0000-0003-3768-877X","id":"3AEC8556-F248-11E8-B48F-1D18A9856A87","last_name":"Tomasek","first_name":"Kathrin"},{"first_name":"Enrique","last_name":"Balleza","full_name":"Balleza, Enrique"},{"last_name":"Kiviet","first_name":"Daniel","full_name":"Kiviet, Daniel"},{"id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9843-3522","first_name":"Robert","last_name":"Hauschild","full_name":"Hauschild, Robert"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik"},{"orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","first_name":"Calin C","full_name":"Guet, Calin C"}],"volume":356,"date_updated":"2024-02-21T13:49:00Z","date_created":"2018-12-11T11:47:48Z","publist_id":"7064","project":[{"name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","doi":"10.1126/science.aaf4762","language":[{"iso":"eng"}],"publication_identifier":{"issn":["00368075"]},"month":"04"},{"scopus_import":"1","article_processing_charge":"No","day":"23","page":"198 - 211","citation":{"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.","apa":"Barone, V., Lang, M., Krens, G., Pradhan, S., Shamipour, S., Sako, K., … Heisenberg, C.-P. J. (2017). An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. Developmental Cell. Cell Press. https://doi.org/10.1016/j.devcel.2017.09.014","ieee":"V. Barone et al., “An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate,” Developmental Cell, vol. 43, no. 2. Cell Press, pp. 198–211, 2017.","ama":"Barone V, Lang M, Krens G, et al. An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. Developmental Cell. 2017;43(2):198-211. doi:10.1016/j.devcel.2017.09.014","chicago":"Barone, Vanessa, Moritz Lang, Gabriel Krens, Saurabh Pradhan, Shayan Shamipour, Keisuke Sako, Mateusz K Sikora, Calin C Guet, and Carl-Philipp J Heisenberg. “An Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling Determines Cell Fate.” Developmental Cell. Cell Press, 2017. https://doi.org/10.1016/j.devcel.2017.09.014.","mla":"Barone, Vanessa, et al. “An Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling Determines Cell Fate.” Developmental Cell, vol. 43, no. 2, Cell Press, 2017, pp. 198–211, doi:10.1016/j.devcel.2017.09.014.","short":"V. Barone, M. Lang, G. Krens, S. Pradhan, S. Shamipour, K. Sako, M.K. Sikora, C.C. Guet, C.-P.J. Heisenberg, Developmental Cell 43 (2017) 198–211."},"publication":"Developmental Cell","date_published":"2017-10-23T00:00:00Z","type":"journal_article","issue":"2","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."}],"intvolume":" 43","title":"An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate","status":"public","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"735","oa_version":"None","publication_identifier":{"issn":["15345807"]},"month":"10","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"},{"_id":"252DD2A6-B435-11E9-9278-68D0E5697425","grant_number":"I2058","name":"Cell segregation in gastrulation: the role of cell fate specification","call_identifier":"FWF"}],"quality_controlled":"1","isi":1,"external_id":{"isi":["000413443700011"]},"language":[{"iso":"eng"}],"doi":"10.1016/j.devcel.2017.09.014","publist_id":"6934","ec_funded":1,"publisher":"Cell Press","department":[{"_id":"CaHe"},{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","year":"2017","volume":43,"date_created":"2018-12-11T11:48:13Z","date_updated":"2024-03-28T23:30:39Z","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"961"},{"id":"8350","status":"public","relation":"dissertation_contains"}]},"author":[{"full_name":"Barone, Vanessa","orcid":"0000-0003-2676-3367","id":"419EECCC-F248-11E8-B48F-1D18A9856A87","last_name":"Barone","first_name":"Vanessa"},{"full_name":"Lang, Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","first_name":"Moritz","last_name":"Lang"},{"full_name":"Krens, Gabriel","id":"2B819732-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4761-5996","first_name":"Gabriel","last_name":"Krens"},{"full_name":"Pradhan, Saurabh","first_name":"Saurabh","last_name":"Pradhan"},{"id":"40B34FE2-F248-11E8-B48F-1D18A9856A87","first_name":"Shayan","last_name":"Shamipour","full_name":"Shamipour, Shayan"},{"orcid":"0000-0002-6453-8075","id":"3BED66BE-F248-11E8-B48F-1D18A9856A87","last_name":"Sako","first_name":"Keisuke","full_name":"Sako, Keisuke"},{"full_name":"Sikora, Mateusz K","id":"2F74BCDE-F248-11E8-B48F-1D18A9856A87","first_name":"Mateusz K","last_name":"Sikora"},{"full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","first_name":"Calin C","last_name":"Guet"},{"full_name":"Heisenberg, Carl-Philipp J","first_name":"Carl-Philipp J","last_name":"Heisenberg","id":"39427864-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-0912-4566"}]},{"language":[{"iso":"eng"}],"conference":{"name":"NIPS: Neural Information Processing Systems","end_date":"2016-12-10","start_date":"2016-12-05","location":"Barcelona, Spain"},"date_published":"2016-12-01T00:00:00Z","quality_controlled":"1","page":"1965-1973","citation":{"chicago":"Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Relevant Sparse Codes with Variational Information Bottleneck,” 29:1965–73. Neural Information Processing Systems, 2016.","short":"M.J. Chalk, O. Marre, G. Tkačik, in:, Neural Information Processing Systems, 2016, pp. 1965–1973.","mla":"Chalk, Matthew J., et al. Relevant Sparse Codes with Variational Information Bottleneck. Vol. 29, Neural Information Processing Systems, 2016, pp. 1965–73.","apa":"Chalk, M. J., Marre, O., & Tkačik, G. (2016). Relevant sparse codes with variational information bottleneck (Vol. 29, pp. 1965–1973). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information Processing Systems.","ieee":"M. J. Chalk, O. Marre, and G. Tkačik, “Relevant sparse codes with variational information bottleneck,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain, 2016, vol. 29, pp. 1965–1973.","ista":"Chalk MJ, Marre O, Tkačik G. 2016. Relevant sparse codes with variational information bottleneck. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 1965–1973.","ama":"Chalk MJ, Marre O, Tkačik G. Relevant sparse codes with variational information bottleneck. In: Vol 29. Neural Information Processing Systems; 2016:1965-1973."},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1605.07332"}],"oa":1,"month":"12","day":"01","scopus_import":1,"date_created":"2018-12-11T11:50:03Z","date_updated":"2021-01-12T06:48:09Z","volume":29,"oa_version":"Preprint","author":[{"first_name":"Matthew J","last_name":"Chalk","id":"2BAAC544-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7782-4436","full_name":"Chalk, Matthew J"},{"last_name":"Marre","first_name":"Olivier","full_name":"Marre, Olivier"},{"last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper"}],"related_material":{"link":[{"relation":"other","url":"https://papers.nips.cc/paper/6101-relevant-sparse-codes-with-variational-information-bottleneck"}]},"title":"Relevant sparse codes with variational information bottleneck","publication_status":"published","status":"public","department":[{"_id":"GaTk"}],"publisher":"Neural Information Processing Systems","intvolume":" 29","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1082","year":"2016","abstract":[{"text":"In many applications, it is desirable to extract only the relevant aspects of data. A principled way to do this is the information bottleneck (IB) method, where one seeks a code that maximises information about a relevance variable, Y, while constraining the information encoded about the original data, X. Unfortunately however, the IB method is computationally demanding when data are high-dimensional and/or non-gaussian. Here we propose an approximate variational scheme for maximising a lower bound on the IB objective, analogous to variational EM. Using this method, we derive an IB algorithm to recover features that are both relevant and sparse. Finally, we demonstrate how kernelised versions of the algorithm can be used to address a broad range of problems with non-linear relation between X and Y.","lang":"eng"}],"publist_id":"6298","alternative_title":["Advances in Neural Information Processing Systems"],"type":"conference"},{"title":"Estimating nonlinear neural response functions using GP priors and Kronecker methods","status":"public","intvolume":" 29","_id":"1105","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa_version":"None","alternative_title":["Advances in Neural Information Processing Systems"],"type":"conference","abstract":[{"lang":"eng","text":"Jointly characterizing neural responses in terms of several external variables promises novel insights into circuit function, but remains computationally prohibitive in practice. Here we use gaussian process (GP) priors and exploit recent advances in fast GP inference and learning based on Kronecker methods, to efficiently estimate multidimensional nonlinear tuning functions. Our estimator require considerably less data than traditional methods and further provides principled uncertainty estimates. We apply these tools to hippocampal recordings during open field exploration and use them to characterize the joint dependence of CA1 responses on the position of the animal and several other variables, including the animal\\'s speed, direction of motion, and network oscillations.Our results provide an unprecedentedly detailed quantification of the tuning of hippocampal neurons. The model\\'s generality suggests that our approach can be used to estimate neural response properties in other brain regions."}],"page":"3610-3618","citation":{"ista":"Savin C, Tkačik G. 2016. Estimating nonlinear neural response functions using GP priors and Kronecker methods. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 3610–3618.","ieee":"C. Savin and G. Tkačik, “Estimating nonlinear neural response functions using GP priors and Kronecker methods,” presented at the NIPS: Neural Information Processing Systems, Barcelona; Spain, 2016, vol. 29, pp. 3610–3618.","apa":"Savin, C., & Tkačik, G. (2016). Estimating nonlinear neural response functions using GP priors and Kronecker methods (Vol. 29, pp. 3610–3618). Presented at the NIPS: Neural Information Processing Systems, Barcelona; Spain: Neural Information Processing Systems.","ama":"Savin C, Tkačik G. Estimating nonlinear neural response functions using GP priors and Kronecker methods. In: Vol 29. Neural Information Processing Systems; 2016:3610-3618.","chicago":"Savin, Cristina, and Gašper Tkačik. “Estimating Nonlinear Neural Response Functions Using GP Priors and Kronecker Methods,” 29:3610–18. Neural Information Processing Systems, 2016.","mla":"Savin, Cristina, and Gašper Tkačik. Estimating Nonlinear Neural Response Functions Using GP Priors and Kronecker Methods. Vol. 29, Neural Information Processing Systems, 2016, pp. 3610–18.","short":"C. Savin, G. Tkačik, in:, Neural Information Processing Systems, 2016, pp. 3610–3618."},"date_published":"2016-12-01T00:00:00Z","scopus_import":1,"day":"01","publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Neural Information Processing Systems","year":"2016","acknowledgement":"We thank Jozsef Csicsvari for kindly sharing the CA1 data.\r\nThis work was supported by the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme(FP7/2007-2013) under REA grant agreement no. 291734.","date_updated":"2021-01-12T06:48:19Z","date_created":"2018-12-11T11:50:10Z","volume":29,"author":[{"full_name":"Savin, Cristina","last_name":"Savin","first_name":"Cristina","id":"3933349E-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper"}],"publist_id":"6265","ec_funded":1,"quality_controlled":"1","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"main_file_link":[{"url":"http://papers.nips.cc/paper/6153-estimating-nonlinear-neural-response-functions-using-gp-priors-and-kronecker-methods"}],"language":[{"iso":"eng"}],"conference":{"end_date":"2016-12-10","start_date":"2016-12-05","location":"Barcelona; Spain","name":"NIPS: Neural Information Processing Systems"},"month":"12"},{"publist_id":"6186","file_date_updated":"2020-07-14T12:44:37Z","volume":38,"date_updated":"2021-01-12T06:48:49Z","date_created":"2018-12-11T11:50:31Z","author":[{"last_name":"Lang","first_name":"Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","full_name":"Lang, Moritz"},{"full_name":"Stelling, Jörg","first_name":"Jörg","last_name":"Stelling"}],"publisher":"Society for Industrial and Applied Mathematics ","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","year":"2016","month":"11","language":[{"iso":"eng"}],"doi":"10.1137/15M103306X","quality_controlled":"1","issue":"6","abstract":[{"text":"The increasing complexity of dynamic models in systems and synthetic biology poses computational challenges especially for the identification of model parameters. While modularization of the corresponding optimization problems could help reduce the “curse of dimensionality,” abundant feedback and crosstalk mechanisms prohibit a simple decomposition of most biomolecular networks into subnetworks, or modules. Drawing on ideas from network modularization and multiple-shooting optimization, we present here a modular parameter identification approach that explicitly allows for such interdependencies. Interfaces between our modules are given by the experimentally measured molecular species. This definition allows deriving good (initial) estimates for the inter-module communication directly from the experimental data. Given these estimates, the states and parameter sensitivities of different modules can be integrated independently. To achieve consistency between modules, we iteratively adjust the estimates for inter-module communication while optimizing the parameters. After convergence to an optimal parameter set---but not during earlier iterations---the intermodule communication as well as the individual modules\\' state dynamics agree with the dynamics of the nonmodularized network. Our modular parameter identification approach allows for easy parallelization; it can reduce the computational complexity for larger networks and decrease the probability to converge to suboptimal local minima. We demonstrate the algorithm\\'s performance in parameter estimation for two biomolecular networks, a synthetic genetic oscillator and a mammalian signaling pathway.","lang":"eng"}],"type":"journal_article","oa_version":"Submitted Version","file":[{"checksum":"781bc3ffd30b2dd65b7727c5a285fc78","date_updated":"2020-07-14T12:44:37Z","date_created":"2018-12-12T10:14:41Z","relation":"main_file","file_id":"5095","content_type":"application/pdf","file_size":871964,"creator":"system","access_level":"local","file_name":"IST-2017-811-v1+1_modular_parameter_identification.pdf"}],"pubrep_id":"811","intvolume":" 38","ddc":["003","518","570","621"],"status":"public","title":"Modular parameter identification of biomolecular networks","_id":"1170","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","has_accepted_license":"1","day":"15","scopus_import":1,"date_published":"2016-11-15T00:00:00Z","page":"B988 - B1008","citation":{"chicago":"Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular Networks.” SIAM Journal on Scientific Computing. Society for Industrial and Applied Mathematics , 2016. https://doi.org/10.1137/15M103306X.","mla":"Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular Networks.” SIAM Journal on Scientific Computing, vol. 38, no. 6, Society for Industrial and Applied Mathematics , 2016, pp. B988–1008, doi:10.1137/15M103306X.","short":"M. Lang, J. Stelling, SIAM Journal on Scientific Computing 38 (2016) B988–B1008.","ista":"Lang M, Stelling J. 2016. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 38(6), B988–B1008.","ieee":"M. Lang and J. Stelling, “Modular parameter identification of biomolecular networks,” SIAM Journal on Scientific Computing, vol. 38, no. 6. Society for Industrial and Applied Mathematics , pp. B988–B1008, 2016.","apa":"Lang, M., & Stelling, J. (2016). Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. Society for Industrial and Applied Mathematics . https://doi.org/10.1137/15M103306X","ama":"Lang M, Stelling J. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 2016;38(6):B988-B1008. doi:10.1137/15M103306X"},"publication":"SIAM Journal on Scientific Computing"},{"month":"07","day":"01","scopus_import":1,"doi":"10.1016/j.plrev.2016.06.005","date_published":"2016-07-01T00:00:00Z","language":[{"iso":"eng"}],"citation":{"ama":"Tkačik G. Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O. C. Martin et al. Physics of Life Reviews. 2016;17:166-167. doi:10.1016/j.plrev.2016.06.005","apa":"Tkačik, G. (2016). Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O. C. Martin et al. Physics of Life Reviews. Elsevier. https://doi.org/10.1016/j.plrev.2016.06.005","ieee":"G. Tkačik, “Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O. C. Martin et al.,” Physics of Life Reviews, vol. 17. Elsevier, pp. 166–167, 2016.","ista":"Tkačik G. 2016. Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O. C. Martin et al. Physics of Life Reviews. 17, 166–167.","short":"G. Tkačik, Physics of Life Reviews 17 (2016) 166–167.","mla":"Tkačik, Gašper. “Understanding Regulatory Networks Requires More than Computing a Multitude of Graph Statistics: Comment on "Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function" by O. C. Martin et Al.” Physics of Life Reviews, vol. 17, Elsevier, 2016, pp. 166–67, doi:10.1016/j.plrev.2016.06.005.","chicago":"Tkačik, Gašper. “Understanding Regulatory Networks Requires More than Computing a Multitude of Graph Statistics: Comment on "Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function" by O. C. Martin et Al.” Physics of Life Reviews. Elsevier, 2016. https://doi.org/10.1016/j.plrev.2016.06.005."},"publication":"Physics of Life Reviews","page":"166 - 167","quality_controlled":"1","publist_id":"6185","type":"journal_article","author":[{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik","full_name":"Tkacik, Gasper"}],"oa_version":"None","volume":17,"date_updated":"2021-01-12T06:48:50Z","date_created":"2018-12-11T11:50:32Z","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1171","year":"2016","department":[{"_id":"GaTk"}],"publisher":"Elsevier","intvolume":" 17","title":"Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O. C. Martin et al.","status":"public","publication_status":"published"},{"citation":{"short":"D. De Martino, D. Masoero, Journal of Statistical Mechanics: Theory and Experiment 2016 (2016).","mla":"De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism & Growth.” Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 12, 123502, IOPscience, 2016, doi:10.1088/1742-5468/aa4e8f.","chicago":"De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism & Growth.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2016. https://doi.org/10.1088/1742-5468/aa4e8f.","ama":"De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. 2016;2016(12). doi:10.1088/1742-5468/aa4e8f","apa":"De Martino, D., & Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa4e8f","ieee":"D. De Martino and D. Masoero, “Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 12. IOPscience, 2016.","ista":"De Martino D, Masoero D. 2016. Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. 2016(12), 123502."},"publication":" Journal of Statistical Mechanics: Theory and Experiment","date_published":"2016-12-30T00:00:00Z","scopus_import":1,"day":"30","_id":"1188","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","intvolume":" 2016","title":"Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth","status":"public","oa_version":"Preprint","type":"journal_article","issue":"12","abstract":[{"text":"We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. \r\nIn the asymptotic regime of slow\r\ndiffusion, that coincides with the relevant experimental range, the resulting\r\nnon-linear Fokker–Planck equation is solved for the steady state in the WKB\r\napproximation that maps it into the ground state of a quantum particle in an\r\nAiry potential plus a centrifugal term. We retrieve scaling laws for growth rate\r\nfluctuations and time response with respect to the distance from the maximum\r\ngrowth rate suggesting that suboptimal populations can have a faster response\r\nto perturbations.","lang":"eng"}],"main_file_link":[{"url":"https://arxiv.org/abs/1606.09048","open_access":"1"}],"oa":1,"project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"quality_controlled":"1","doi":"10.1088/1742-5468/aa4e8f","language":[{"iso":"eng"}],"month":"12","year":"2016","acknowledgement":"D De Martino is supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. D Masoero is supported by the FCT scholarship, number SFRH/BPD/75908/2011. D De Martino thanks the Grupo de Física Matemática of the Universidade de Lisboa for the kind hospitality. We also wish to thank Matteo Osella, Vincenzo Vitagliano and Vera Luz Masoero for useful discussions, also late at night.","publisher":"IOPscience","department":[{"_id":"GaTk"}],"publication_status":"published","author":[{"full_name":"De Martino, Daniele","first_name":"Daniele","last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706"},{"full_name":"Masoero, Davide","last_name":"Masoero","first_name":"Davide"}],"volume":2016,"date_updated":"2021-01-12T06:48:57Z","date_created":"2018-12-11T11:50:37Z","article_number":"123502","publist_id":"6165","ec_funded":1},{"publist_id":"6146","author":[{"first_name":"Fang","last_name":"Hu","full_name":"Hu, Fang"},{"last_name":"Rishishwar","first_name":"Lavanya","full_name":"Rishishwar, Lavanya"},{"first_name":"Ambily","last_name":"Sivadas","full_name":"Sivadas, Ambily"},{"last_name":"Mitchell","first_name":"Gabriel","id":"315BCD80-F248-11E8-B48F-1D18A9856A87","full_name":"Mitchell, Gabriel"},{"full_name":"King, Jordan","first_name":"Jordan","last_name":"King"},{"full_name":"Murphy, Timothy","first_name":"Timothy","last_name":"Murphy"},{"full_name":"Gilsdorf, Janet","last_name":"Gilsdorf","first_name":"Janet"},{"last_name":"Mayer","first_name":"Leonard","full_name":"Mayer, Leonard"},{"full_name":"Wang, Xin","first_name":"Xin","last_name":"Wang"}],"volume":54,"date_created":"2018-12-11T11:50:41Z","date_updated":"2021-01-12T06:49:04Z","year":"2016","acknowledgement":"We are grateful to ABCs for providing strains and the Bacterial Meningitis Laboratory for technical support.","department":[{"_id":"GaTk"}],"publisher":"American Society for Microbiology","publication_status":"published","month":"12","doi":"10.1128/JCM.01511-16","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5121393/"}],"oa":1,"quality_controlled":"1","issue":"12","abstract":[{"text":"Haemophilus haemolyticus has been recently discovered to have the potential to cause invasive disease. It is closely related to nontypeable Haemophilus influenzae (NT H. influenzae). NT H. influenzae and H. haemolyticus are often misidentified because none of the existing tests targeting the known phenotypes of H. haemolyticus are able to specifically identify H. haemolyticus. Through comparative genomic analysis of H. haemolyticus and NT H. influenzae, we identified genes unique to H. haemolyticus that can be used as targets for the identification of H. haemolyticus. A real-time PCR targeting purT (encoding phosphoribosylglycinamide formyltransferase 2 in the purine synthesis pathway) was developed and evaluated. The lower limit of detection was 40 genomes/PCR; the sensitivity and specificity in detecting H. haemolyticus were 98.9% and 97%, respectively. To improve the discrimination of H. haemolyticus and NT H. influenzae, a testing scheme combining two targets (H. haemolyticus purT and H. influenzae hpd, encoding protein D lipoprotein) was also evaluated and showed 96.7% sensitivity and 98.2% specificity for the identification of H. haemolyticus and 92.8% sensitivity and 100% specificity for the identification of H. influenzae, respectively. The dual-target testing scheme can be used for the diagnosis and surveillance of infection and disease caused by H. haemolyticus and NT H. influenzae.","lang":"eng"}],"type":"journal_article","oa_version":"Submitted Version","_id":"1203","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","intvolume":" 54","status":"public","title":"Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination","day":"01","scopus_import":1,"date_published":"2016-12-01T00:00:00Z","citation":{"chicago":"Hu, Fang, Lavanya Rishishwar, Ambily Sivadas, Gabriel Mitchell, Jordan King, Timothy Murphy, Janet Gilsdorf, Leonard Mayer, and Xin Wang. “Comparative Genomic Analysis of Haemophilus Haemolyticus and Nontypeable Haemophilus Influenzae and a New Testing Scheme for Their Discrimination.” Journal of Clinical Microbiology. American Society for Microbiology, 2016. https://doi.org/10.1128/JCM.01511-16.","mla":"Hu, Fang, et al. “Comparative Genomic Analysis of Haemophilus Haemolyticus and Nontypeable Haemophilus Influenzae and a New Testing Scheme for Their Discrimination.” Journal of Clinical Microbiology, vol. 54, no. 12, American Society for Microbiology, 2016, pp. 3010–17, doi:10.1128/JCM.01511-16.","short":"F. Hu, L. Rishishwar, A. Sivadas, G. Mitchell, J. King, T. Murphy, J. Gilsdorf, L. Mayer, X. Wang, Journal of Clinical Microbiology 54 (2016) 3010–3017.","ista":"Hu F, Rishishwar L, Sivadas A, Mitchell G, King J, Murphy T, Gilsdorf J, Mayer L, Wang X. 2016. Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. 54(12), 3010–3017.","ieee":"F. Hu et al., “Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination,” Journal of Clinical Microbiology, vol. 54, no. 12. American Society for Microbiology, pp. 3010–3017, 2016.","apa":"Hu, F., Rishishwar, L., Sivadas, A., Mitchell, G., King, J., Murphy, T., … Wang, X. (2016). Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. American Society for Microbiology. https://doi.org/10.1128/JCM.01511-16","ama":"Hu F, Rishishwar L, Sivadas A, et al. Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. 2016;54(12):3010-3017. doi:10.1128/JCM.01511-16"},"publication":"Journal of Clinical Microbiology","page":"3010 - 3017"},{"year":"2016","_id":"1214","acknowledgement":"RD thanks for the hospitality at the Max-Planck-Institute and for helpful discussions with Nihat Ay and Keyan Zahedi.","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publisher":"IEEE","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"title":"Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm","status":"public","publication_status":"published","author":[{"full_name":"Martius, Georg S","id":"3A276B68-F248-11E8-B48F-1D18A9856A87","first_name":"Georg S","last_name":"Martius"},{"first_name":"Raphael","last_name":"Hostettler","full_name":"Hostettler, Raphael"},{"full_name":"Knoll, Alois","last_name":"Knoll","first_name":"Alois"},{"full_name":"Der, Ralf","last_name":"Der","first_name":"Ralf"}],"volume":"2016-November","oa_version":"None","date_updated":"2021-01-12T06:49:08Z","date_created":"2018-12-11T11:50:45Z","type":"conference","article_number":"7759138","publist_id":"6121","abstract":[{"lang":"eng","text":"With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. While very successful with classical robots, these methods run into severe difficulties when applied to soft robots, a new field of robotics with large interest for human-robot interaction. We claim that a novel controller paradigm opens new perspective for this field. This paper applies a recently developed neuro controller with differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object's internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently develops to rotate it. In this way, the robot discovers affordances of objects its body is interacting with."}],"citation":{"mla":"Martius, Georg S., et al. Compliant Control for Soft Robots: Emergent Behavior of a Tendon Driven Anthropomorphic Arm. Vol. 2016–November, 7759138, IEEE, 2016, doi:10.1109/IROS.2016.7759138.","short":"G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, IEEE, 2016.","chicago":"Martius, Georg S, Raphael Hostettler, Alois Knoll, and Ralf Der. “Compliant Control for Soft Robots: Emergent Behavior of a Tendon Driven Anthropomorphic Arm,” Vol. 2016–November. IEEE, 2016. https://doi.org/10.1109/IROS.2016.7759138.","ama":"Martius GS, Hostettler R, Knoll A, Der R. Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm. In: Vol 2016-November. IEEE; 2016. doi:10.1109/IROS.2016.7759138","ista":"Martius GS, Hostettler R, Knoll A, Der R. 2016. Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm. IEEE RSJ International Conference on Intelligent Robots and Systems IROS vol. 2016–November, 7759138.","apa":"Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm (Vol. 2016–November). Presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea: IEEE. https://doi.org/10.1109/IROS.2016.7759138","ieee":"G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm,” presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea, 2016, vol. 2016–November."},"quality_controlled":"1","doi":"10.1109/IROS.2016.7759138","date_published":"2016-11-28T00:00:00Z","conference":{"name":"IEEE RSJ International Conference on Intelligent Robots and Systems IROS ","start_date":"2016-09-09","location":"Daejeon, Korea","end_date":"2016-09-14"},"language":[{"iso":"eng"}],"scopus_import":1,"day":"28","month":"11"},{"language":[{"iso":"eng"}],"conference":{"end_date":"2016-06-17","start_date":"2016-06-13","location":"Washington, D.C., USA","name":"AIAA: Aviation Technology, Integration, and Operations Conference"},"date_published":"2016-06-01T00:00:00Z","doi":"10.2514/6.2016-3764","quality_controlled":"1","page":"1 - 19","citation":{"apa":"Mikić, G., Stoll, A., Bevirt, J., Grah, R., & Moore, M. (2016). Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency (pp. 1–19). Presented at the AIAA: Aviation Technology, Integration, and Operations Conference, Washington, D.C., USA: AIAA. https://doi.org/10.2514/6.2016-3764","ieee":"G. Mikić, A. Stoll, J. Bevirt, R. Grah, and M. Moore, “Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency,” presented at the AIAA: Aviation Technology, Integration, and Operations Conference, Washington, D.C., USA, 2016, pp. 1–19.","ista":"Mikić G, Stoll A, Bevirt J, Grah R, Moore M. 2016. Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency. AIAA: Aviation Technology, Integration, and Operations Conference, 1–19.","ama":"Mikić G, Stoll A, Bevirt J, Grah R, Moore M. Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency. In: AIAA; 2016:1-19. doi:10.2514/6.2016-3764","chicago":"Mikić, Gregor, Alex Stoll, Joe Bevirt, Rok Grah, and Mark Moore. “Fuselage Boundary Layer Ingestion Propulsion Applied to a Thin Haul Commuter Aircraft for Optimal Efficiency,” 1–19. AIAA, 2016. https://doi.org/10.2514/6.2016-3764.","short":"G. Mikić, A. Stoll, J. Bevirt, R. Grah, M. Moore, in:, AIAA, 2016, pp. 1–19.","mla":"Mikić, Gregor, et al. Fuselage Boundary Layer Ingestion Propulsion Applied to a Thin Haul Commuter Aircraft for Optimal Efficiency. AIAA, 2016, pp. 1–19, doi:10.2514/6.2016-3764."},"oa":1,"main_file_link":[{"url":"https://ntrs.nasa.gov/search.jsp?R=20160010167&hterms=Fuselage+boundary+layer+ingestion+propulsion+applied+thin+haul+commuter+aircraft+optimal+efficiency&qs=N%3D0%26Ntk%3DAll%26Ntt%3DFuselage%2520boundary%2520layer%2520ingestion%2520propulsion%2520applied%2520to%2520a%2520thin%2520haul%2520commuter%2520aircraft%2520for%2520optimal%2520efficiency%26Ntx%3Dmode%2520matchallpartial%26Nm%3D123%7CCollection%7CNASA%2520STI%7C%7C17%7CCollection%7CNACA","open_access":"1"}],"day":"01","month":"06","scopus_import":1,"date_created":"2018-12-11T11:50:47Z","date_updated":"2023-02-21T10:17:50Z","oa_version":"Preprint","author":[{"full_name":"Mikić, Gregor","first_name":"Gregor","last_name":"Mikić"},{"full_name":"Stoll, Alex","first_name":"Alex","last_name":"Stoll"},{"last_name":"Bevirt","first_name":"Joe","full_name":"Bevirt, Joe"},{"id":"483E70DE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2539-3560","first_name":"Rok","last_name":"Grah","full_name":"Grah, Rok"},{"full_name":"Moore, Mark","first_name":"Mark","last_name":"Moore"}],"status":"public","title":"Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency","publication_status":"published","publisher":"AIAA","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"_id":"1220","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","year":"2016","abstract":[{"lang":"eng","text":"Theoretical and numerical aspects of aerodynamic efficiency of propulsion systems coupled to the boundary layer of a fuselage are studied. We discuss the effects of local flow fields, which are affected both by conservative flow acceleration as well as total pressure losses, on the efficiency of boundary layer immersed propulsion devices. We introduce the concept of a boundary layer retardation turbine that helps reduce skin friction over the fuselage. We numerically investigate efficiency gains offered by boundary layer and wake interacting devices. We discuss the results in terms of a total energy consumption framework and show that efficiency gains of any device depend on all the other elements of the propulsion system."}],"publist_id":"6114","type":"conference"},{"volume":93,"date_created":"2018-12-11T11:50:54Z","date_updated":"2021-01-12T06:49:20Z","author":[{"full_name":"Sokolowski, Thomas R","last_name":"Sokolowski","first_name":"Thomas R","orcid":"0000-0002-1287-3779","id":"3E999752-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Walczak, Aleksandra","first_name":"Aleksandra","last_name":"Walczak"},{"full_name":"Bialek, William","first_name":"William","last_name":"Bialek"},{"full_name":"Tkacik, Gasper","last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"}],"department":[{"_id":"GaTk"}],"publisher":"American Institute of Physics","publication_status":"published","acknowledgement":"We thank T. Gregor, A. Prochaintz, and others for\r\nhelpful discussions. This work was supported in part by\r\nGrants No. PHY-1305525 and No. CCF-0939370 from the\r\nUS National Science Foundation and by the W.M. Keck\r\nFoundation. A.M.W. acknowledges the support by European\r\nResearch Council (ERC) Grant No. MCCIG PCIG10–GA-\r\n2011–303561. G.T. and T.R.S. were supported by Austrian\r\nScience Fund (FWF) Grant No. P28844S.","year":"2016","publist_id":"6088","article_number":"022404","language":[{"iso":"eng"}],"doi":"10.1103/PhysRevE.93.022404","project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation"}],"quality_controlled":"1","oa":1,"main_file_link":[{"url":"https://arxiv.org/abs/1507.02562","open_access":"1"}],"month":"02","oa_version":"Preprint","intvolume":" 93","title":"Extending the dynamic range of transcription factor action by translational regulation","status":"public","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1242","issue":"2","abstract":[{"text":"A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression.","lang":"eng"}],"type":"journal_article","date_published":"2016-02-04T00:00:00Z","citation":{"chicago":"Sokolowski, Thomas R, Aleksandra Walczak, William Bialek, and Gašper Tkačik. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics, 2016. https://doi.org/10.1103/PhysRevE.93.022404.","short":"T.R. Sokolowski, A. Walczak, W. Bialek, G. Tkačik, Physical Review E Statistical Nonlinear and Soft Matter Physics 93 (2016).","mla":"Sokolowski, Thomas R., et al. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 93, no. 2, 022404, American Institute of Physics, 2016, doi:10.1103/PhysRevE.93.022404.","apa":"Sokolowski, T. R., Walczak, A., Bialek, W., & Tkačik, G. (2016). Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.93.022404","ieee":"T. R. Sokolowski, A. Walczak, W. Bialek, and G. Tkačik, “Extending the dynamic range of transcription factor action by translational regulation,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 93, no. 2. American Institute of Physics, 2016.","ista":"Sokolowski TR, Walczak A, Bialek W, Tkačik G. 2016. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. 93(2), 022404.","ama":"Sokolowski TR, Walczak A, Bialek W, Tkačik G. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2016;93(2). doi:10.1103/PhysRevE.93.022404"},"publication":"Physical Review E Statistical Nonlinear and Soft Matter Physics","day":"04","scopus_import":1},{"author":[{"full_name":"Recouvreux, Pierre","first_name":"Pierre","last_name":"Recouvreux"},{"full_name":"Sokolowski, Thomas R","first_name":"Thomas R","last_name":"Sokolowski","id":"3E999752-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-1287-3779"},{"full_name":"Grammoustianou, Aristea","last_name":"Grammoustianou","first_name":"Aristea"},{"full_name":"Tenwolde, Pieter","first_name":"Pieter","last_name":"Tenwolde"},{"last_name":"Dogterom","first_name":"Marileen","full_name":"Dogterom, Marileen"}],"date_updated":"2021-01-12T06:49:21Z","date_created":"2018-12-11T11:50:55Z","volume":113,"year":"2016","acknowledgement":"We thank Sophie Martin, Ken Sawin, Stephen Huisman,\r\nand Damian Brunner for strains; Julianne\r\nTeapal, Marcel Janson, Sergio Rincon,\r\nand Phong Tran for technical assistance; Andrew Mugler and Bela Mulder for\r\ndiscussions; and Sander Tans, Phong Tran,\r\nand Anne Paoletti for critical reading\r\nof the manuscript. This work is part of the research program of the\r\n“\r\nStichting\r\nvoor Fundamenteel Onderzoek de Materie,\r\n”\r\nwhich is financially supported by\r\nthe\r\n“\r\nNederlandse organisatie voor Wete\r\nnschappelijk Onderzoek (NWO).\r\n”","publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"National Academy of Sciences","publist_id":"6085","doi":"10.1073/pnas.1419248113","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763754/","open_access":"1"}],"oa":1,"quality_controlled":"1","month":"02","oa_version":"Submitted Version","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1244","title":"Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells","status":"public","intvolume":" 113","abstract":[{"lang":"eng","text":"Cell polarity refers to a functional spatial organization of proteins that is crucial for the control of essential cellular processes such as growth and division. To establish polarity, cells rely on elaborate regulation networks that control the distribution of proteins at the cell membrane. In fission yeast cells, a microtubule-dependent network has been identified that polarizes the distribution of signaling proteins that restricts growth to cell ends and targets the cytokinetic machinery to the middle of the cell. Although many molecular components have been shown to play a role in this network, it remains unknown which molecular functionalities are minimally required to establish a polarized protein distribution in this system. Here we show that a membrane-binding protein fragment, which distributes homogeneously in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching it to a cytoplasmic microtubule end-binding protein. This concentration results in a polarized pattern of chimera proteins with a spatial extension that is very reminiscent of natural polarity patterns in fission yeast. However, chimera levels fluctuate in response to microtubule dynamics, and disruption of microtubules leads to disappearance of the pattern. Numerical simulations confirm that the combined functionality of membrane anchoring and microtubule tip affinity is in principle sufficient to create polarized patterns. Our chimera protein may thus represent a simple molecular functionality that is able to polarize the membrane, onto which additional layers of molecular complexity may be built to provide the temporal robustness that is typical of natural polarity patterns."}],"issue":"7","type":"journal_article","date_published":"2016-02-16T00:00:00Z","publication":"PNAS","citation":{"ista":"Recouvreux P, Sokolowski TR, Grammoustianou A, Tenwolde P, Dogterom M. 2016. Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. 113(7), 1811–1816.","apa":"Recouvreux, P., Sokolowski, T. R., Grammoustianou, A., Tenwolde, P., & Dogterom, M. (2016). Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1419248113","ieee":"P. Recouvreux, T. R. Sokolowski, A. Grammoustianou, P. Tenwolde, and M. Dogterom, “Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells,” PNAS, vol. 113, no. 7. National Academy of Sciences, pp. 1811–1816, 2016.","ama":"Recouvreux P, Sokolowski TR, Grammoustianou A, Tenwolde P, Dogterom M. Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. 2016;113(7):1811-1816. doi:10.1073/pnas.1419248113","chicago":"Recouvreux, Pierre, Thomas R Sokolowski, Aristea Grammoustianou, Pieter Tenwolde, and Marileen Dogterom. “Chimera Proteins with Affinity for Membranes and Microtubule Tips Polarize in the Membrane of Fission Yeast Cells.” PNAS. National Academy of Sciences, 2016. https://doi.org/10.1073/pnas.1419248113.","mla":"Recouvreux, Pierre, et al. “Chimera Proteins with Affinity for Membranes and Microtubule Tips Polarize in the Membrane of Fission Yeast Cells.” PNAS, vol. 113, no. 7, National Academy of Sciences, 2016, pp. 1811–16, doi:10.1073/pnas.1419248113.","short":"P. Recouvreux, T.R. Sokolowski, A. Grammoustianou, P. Tenwolde, M. Dogterom, PNAS 113 (2016) 1811–1816."},"page":"1811 - 1816","day":"16","scopus_import":1},{"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1248","status":"public","title":"Information processing in living systems","intvolume":" 7","oa_version":"Preprint","type":"journal_article","abstract":[{"text":"Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been possible to measure, directly, the flow of information in biological networks, or more generally where information-theoretic ideas have been used to guide the analysis of experiments. Systems of interest range from single molecules (the sequence diversity in families of proteins) to groups of organisms (the distribution of velocities in flocks of birds), and all scales in between. Many of these analyses are motivated by the idea that biological systems may have evolved to optimize the gathering and representation of information, and we review the experimental evidence for this optimization, again across a wide range of scales.","lang":"eng"}],"publication":"Annual Review of Condensed Matter Physics","citation":{"ieee":"G. Tkačik and W. Bialek, “Information processing in living systems,” Annual Review of Condensed Matter Physics, vol. 7. Annual Reviews, pp. 89–117, 2016.","apa":"Tkačik, G., & Bialek, W. (2016). Information processing in living systems. Annual Review of Condensed Matter Physics. Annual Reviews. https://doi.org/10.1146/annurev-conmatphys-031214-014803","ista":"Tkačik G, Bialek W. 2016. Information processing in living systems. Annual Review of Condensed Matter Physics. 7, 89–117.","ama":"Tkačik G, Bialek W. Information processing in living systems. Annual Review of Condensed Matter Physics. 2016;7:89-117. doi:10.1146/annurev-conmatphys-031214-014803","chicago":"Tkačik, Gašper, and William Bialek. “Information Processing in Living Systems.” Annual Review of Condensed Matter Physics. Annual Reviews, 2016. https://doi.org/10.1146/annurev-conmatphys-031214-014803.","short":"G. Tkačik, W. Bialek, Annual Review of Condensed Matter Physics 7 (2016) 89–117.","mla":"Tkačik, Gašper, and William Bialek. “Information Processing in Living Systems.” Annual Review of Condensed Matter Physics, vol. 7, Annual Reviews, 2016, pp. 89–117, doi:10.1146/annurev-conmatphys-031214-014803."},"page":"89 - 117","date_published":"2016-03-10T00:00:00Z","scopus_import":1,"day":"10","year":"2016","acknowledgement":"Our work was supported in part by the US\r\nNational Science Foundation (PHY–1305525 and CCF–\r\n0939370), by the Austrian Science Foundation (FWF\r\nP25651), by the Human Frontiers Science Program, and\r\nby the Simons and Swartz Foundations.","publication_status":"published","publisher":"Annual Reviews","department":[{"_id":"GaTk"}],"author":[{"full_name":"Tkacik, Gasper","last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Bialek","first_name":"William","full_name":"Bialek, William"}],"date_updated":"2021-01-12T06:49:23Z","date_created":"2018-12-11T11:50:56Z","volume":7,"publist_id":"6080","oa":1,"main_file_link":[{"url":"https://arxiv.org/abs/1412.8752","open_access":"1"}],"quality_controlled":"1","project":[{"grant_number":"P 25651-N26","_id":"254D1A94-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Sensitivity to higher-order statistics in natural scenes"}],"doi":"10.1146/annurev-conmatphys-031214-014803","language":[{"iso":"eng"}],"month":"03"},{"article_processing_charge":"No","day":"01","scopus_import":1,"date_published":"2016-06-01T00:00:00Z","article_type":"original","citation":{"apa":"De Martino, D. (2016). The dual of the space of interactions in neural network models. International Journal of Modern Physics C. World Scientific Publishing. https://doi.org/10.1142/S0129183116500674","ieee":"D. De Martino, “The dual of the space of interactions in neural network models,” International Journal of Modern Physics C, vol. 27, no. 6. World Scientific Publishing, 2016.","ista":"De Martino D. 2016. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 27(6), 1650067.","ama":"De Martino D. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 2016;27(6). doi:10.1142/S0129183116500674","chicago":"De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network Models.” International Journal of Modern Physics C. World Scientific Publishing, 2016. https://doi.org/10.1142/S0129183116500674.","short":"D. De Martino, International Journal of Modern Physics C 27 (2016).","mla":"De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network Models.” International Journal of Modern Physics C, vol. 27, no. 6, 1650067, World Scientific Publishing, 2016, doi:10.1142/S0129183116500674."},"publication":"International Journal of Modern Physics C","issue":"6","abstract":[{"lang":"eng","text":"In this work, the Gardner problem of inferring interactions and fields for an Ising neural network from given patterns under a local stability hypothesis is addressed under a dual perspective. By means of duality arguments, an integer linear system is defined whose solution space is the dual of the Gardner space and whose solutions represent mutually unstable patterns. We propose and discuss Monte Carlo methods in order to find and remove unstable patterns and uniformly sample the space of interactions thereafter. We illustrate the problem on a set of real data and perform ensemble calculation that shows how the emergence of phase dominated by unstable patterns can be triggered in a nonlinear discontinuous way."}],"type":"journal_article","oa_version":"Preprint","intvolume":" 27","status":"public","title":"The dual of the space of interactions in neural network models","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1260","month":"06","language":[{"iso":"eng"}],"doi":"10.1142/S0129183116500674","quality_controlled":"1","main_file_link":[{"url":"https://arxiv.org/abs/1505.02963","open_access":"1"}],"oa":1,"external_id":{"arxiv":["1505.02963"]},"publist_id":"6065","article_number":"1650067","volume":27,"date_updated":"2021-01-12T06:49:28Z","date_created":"2018-12-11T11:51:00Z","author":[{"full_name":"De Martino, Daniele","orcid":"0000-0002-5214-4706","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","last_name":"De Martino","first_name":"Daniele"}],"publisher":"World Scientific Publishing","department":[{"_id":"GaTk"}],"publication_status":"published","year":"2016"},{"citation":{"ama":"Chalk MJ, Gutkin B, Denève S. Neural oscillations as a signature of efficient coding in the presence of synaptic delays. eLife. 2016;5(2016JULY). doi:10.7554/eLife.13824","ista":"Chalk MJ, Gutkin B, Denève S. 2016. Neural oscillations as a signature of efficient coding in the presence of synaptic delays. eLife. 5(2016JULY), e13824.","apa":"Chalk, M. J., Gutkin, B., & Denève, S. (2016). Neural oscillations as a signature of efficient coding in the presence of synaptic delays. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.13824","ieee":"M. J. Chalk, B. Gutkin, and S. Denève, “Neural oscillations as a signature of efficient coding in the presence of synaptic delays,” eLife, vol. 5, no. 2016JULY. eLife Sciences Publications, 2016.","mla":"Chalk, Matthew J., et al. “Neural Oscillations as a Signature of Efficient Coding in the Presence of Synaptic Delays.” ELife, vol. 5, no. 2016JULY, e13824, eLife Sciences Publications, 2016, doi:10.7554/eLife.13824.","short":"M.J. Chalk, B. Gutkin, S. Denève, ELife 5 (2016).","chicago":"Chalk, Matthew J, Boris Gutkin, and Sophie Denève. “Neural Oscillations as a Signature of Efficient Coding in the Presence of Synaptic Delays.” ELife. eLife Sciences Publications, 2016. https://doi.org/10.7554/eLife.13824."},"publication":"eLife","date_published":"2016-07-01T00:00:00Z","scopus_import":1,"has_accepted_license":"1","day":"01","intvolume":" 5","title":"Neural oscillations as a signature of efficient coding in the presence of synaptic delays","status":"public","ddc":["571"],"_id":"1266","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","file":[{"access_level":"open_access","file_name":"IST-2016-700-v1+1_e13824-download.pdf","file_size":2819055,"content_type":"application/pdf","creator":"system","relation":"main_file","file_id":"4874","checksum":"dc52d967dc76174477bb258d84be2899","date_created":"2018-12-12T10:11:20Z","date_updated":"2020-07-14T12:44:42Z"}],"pubrep_id":"700","type":"journal_article","issue":"2016JULY","abstract":[{"lang":"eng","text":"Cortical networks exhibit ‘global oscillations’, in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a ‘prediction error’ while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code."}],"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"language":[{"iso":"eng"}],"doi":"10.7554/eLife.13824","month":"07","publisher":"eLife Sciences Publications","department":[{"_id":"GaTk"}],"publication_status":"published","year":"2016","acknowledgement":"Boris Gutkin acknowledges funding by the Russian Academic Excellence Project '5-100’.","volume":5,"date_created":"2018-12-11T11:51:02Z","date_updated":"2021-01-12T06:49:30Z","author":[{"full_name":"Chalk, Matthew J","orcid":"0000-0001-7782-4436","id":"2BAAC544-F248-11E8-B48F-1D18A9856A87","last_name":"Chalk","first_name":"Matthew J"},{"first_name":"Boris","last_name":"Gutkin","full_name":"Gutkin, Boris"},{"full_name":"Denève, Sophie","last_name":"Denève","first_name":"Sophie"}],"article_number":"e13824","publist_id":"6056","file_date_updated":"2020-07-14T12:44:42Z"},{"quality_controlled":"1","oa":1,"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069154/"}],"language":[{"iso":"eng"}],"doi":"10.1038/nchembio.2176","month":"11","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"Nature Publishing Group","publication_status":"published","acknowledgement":"This work was supported in part by National Institute of Allergy and Infectious Diseases grant U54 AI057159, US National Institutes of Health grants R01 GM081617 (to R.K.) and GM086258 (to J.C.), European Research Council FP7 ERC grant 281891 (to R.K.) and a National Science Foundation Graduate Fellowship (to L.K.S.).\r\n","year":"2016","volume":12,"date_created":"2018-12-11T11:51:10Z","date_updated":"2021-01-12T06:49:39Z","author":[{"full_name":"Stone, Laura","last_name":"Stone","first_name":"Laura"},{"last_name":"Baym","first_name":"Michael","full_name":"Baym, Michael"},{"full_name":"Lieberman, Tami","first_name":"Tami","last_name":"Lieberman"},{"full_name":"Chait, Remy P","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-0876-3187","first_name":"Remy P","last_name":"Chait"},{"first_name":"Jon","last_name":"Clardy","full_name":"Clardy, Jon"},{"last_name":"Kishony","first_name":"Roy","full_name":"Kishony, Roy"}],"publist_id":"6026","page":"902 - 904","citation":{"ama":"Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. 2016;12(11):902-904. doi:10.1038/nchembio.2176","ieee":"L. Stone, M. Baym, T. Lieberman, R. P. Chait, J. Clardy, and R. Kishony, “Compounds that select against the tetracycline-resistance efflux pump,” Nature Chemical Biology, vol. 12, no. 11. Nature Publishing Group, pp. 902–904, 2016.","apa":"Stone, L., Baym, M., Lieberman, T., Chait, R. P., Clardy, J., & Kishony, R. (2016). Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. Nature Publishing Group. https://doi.org/10.1038/nchembio.2176","ista":"Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. 2016. Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. 12(11), 902–904.","short":"L. Stone, M. Baym, T. Lieberman, R.P. Chait, J. Clardy, R. Kishony, Nature Chemical Biology 12 (2016) 902–904.","mla":"Stone, Laura, et al. “Compounds That Select against the Tetracycline-Resistance Efflux Pump.” Nature Chemical Biology, vol. 12, no. 11, Nature Publishing Group, 2016, pp. 902–04, doi:10.1038/nchembio.2176.","chicago":"Stone, Laura, Michael Baym, Tami Lieberman, Remy P Chait, Jon Clardy, and Roy Kishony. “Compounds That Select against the Tetracycline-Resistance Efflux Pump.” Nature Chemical Biology. Nature Publishing Group, 2016. https://doi.org/10.1038/nchembio.2176."},"publication":"Nature Chemical Biology","date_published":"2016-11-01T00:00:00Z","scopus_import":1,"day":"01","intvolume":" 12","status":"public","title":"Compounds that select against the tetracycline-resistance efflux pump","_id":"1290","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa_version":"Preprint","type":"journal_article","issue":"11","abstract":[{"lang":"eng","text":"We developed a competition-based screening strategy to identify compounds that invert the selective advantage of antibiotic resistance. Using our assay, we screened over 19,000 compounds for the ability to select against the TetA tetracycline-resistance efflux pump in Escherichia coli and identified two hits, β-thujaplicin and disulfiram. Treating a tetracycline-resistant population with β-thujaplicin selects for loss of the resistance gene, enabling an effective second-phase treatment with doxycycline."}]},{"ddc":["003","621"],"title":"Scale-invariant systems realize nonlinear differential operators","status":"public","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1320","file":[{"checksum":"7219432b43defc62a0d45f48d4ce6a19","date_created":"2018-12-12T10:16:17Z","date_updated":"2020-07-14T12:44:43Z","file_id":"5203","relation":"main_file","creator":"system","content_type":"application/pdf","file_size":539166,"access_level":"local","file_name":"IST-2017-810-v1+1_root.pdf"}],"oa_version":"Preprint","pubrep_id":"810","type":"conference","abstract":[{"text":"In recent years, several biomolecular systems have been shown to be scale-invariant (SI), i.e. to show the same output dynamics when exposed to geometrically scaled input signals (u → pu, p > 0) after pre-adaptation to accordingly scaled constant inputs. In this article, we show that SI systems-as well as systems invariant with respect to other input transformations-can realize nonlinear differential operators: when excited by inputs obeying functional forms characteristic for a given class of invariant systems, the systems' outputs converge to constant values directly quantifying the speed of the input.","lang":"eng"}],"citation":{"short":"M. Lang, E. Sontag, in:, IEEE, 2016.","mla":"Lang, Moritz, and Eduardo Sontag. Scale-Invariant Systems Realize Nonlinear Differential Operators. Vol. 2016–July, 7526722, IEEE, 2016, doi:10.1109/ACC.2016.7526722.","chicago":"Lang, Moritz, and Eduardo Sontag. “Scale-Invariant Systems Realize Nonlinear Differential Operators,” Vol. 2016–July. IEEE, 2016. https://doi.org/10.1109/ACC.2016.7526722.","ama":"Lang M, Sontag E. Scale-invariant systems realize nonlinear differential operators. In: Vol 2016-July. IEEE; 2016. doi:10.1109/ACC.2016.7526722","ieee":"M. Lang and E. Sontag, “Scale-invariant systems realize nonlinear differential operators,” presented at the ACC: American Control Conference, Boston, MA, USA, 2016, vol. 2016–July.","apa":"Lang, M., & Sontag, E. (2016). Scale-invariant systems realize nonlinear differential operators (Vol. 2016–July). Presented at the ACC: American Control Conference, Boston, MA, USA: IEEE. https://doi.org/10.1109/ACC.2016.7526722","ista":"Lang M, Sontag E. 2016. Scale-invariant systems realize nonlinear differential operators. ACC: American Control Conference vol. 2016–July, 7526722."},"date_published":"2016-07-28T00:00:00Z","scopus_import":1,"day":"28","has_accepted_license":"1","publication_status":"published","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"IEEE","acknowledgement":"The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement n° [291734]. Work supported in part by grants AFOSR FA9550-14-1-0060 and NIH 1R01GM100473.","year":"2016","date_created":"2018-12-11T11:51:21Z","date_updated":"2021-01-12T06:49:51Z","volume":"2016-July","author":[{"full_name":"Lang, Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","first_name":"Moritz","last_name":"Lang"},{"first_name":"Eduardo","last_name":"Sontag","full_name":"Sontag, Eduardo"}],"article_number":"7526722","file_date_updated":"2020-07-14T12:44:43Z","ec_funded":1,"publist_id":"5950","quality_controlled":"1","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"language":[{"iso":"eng"}],"conference":{"name":"ACC: American Control Conference","location":"Boston, MA, USA","start_date":"2016-07-06","end_date":"2016-07-08"},"doi":"10.1109/ACC.2016.7526722","month":"07"},{"abstract":[{"lang":"eng","text":"Antibiotic-sensitive and -resistant bacteria coexist in natural environments with low, if detectable, antibiotic concentrations. Except possibly around localized antibiotic sources, where resistance can provide a strong advantage, bacterial fitness is dominated by stresses unaffected by resistance to the antibiotic. How do such mixed and heterogeneous conditions influence the selective advantage or disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels of tetracyclines potentiate selection for or against tetracycline resistance around localized sources of almost any toxin or stress. Furthermore, certain stresses generate alternating rings of selection for and against resistance around a localized source of the antibiotic. In these conditions, localized antibiotic sources, even at high strengths, can actually produce a net selection against resistance to the antibiotic. Our results show that interactions between the effects of an antibiotic and other stresses in inhomogeneous environments can generate pervasive, complex patterns of selection both for and against antibiotic resistance."}],"type":"journal_article","pubrep_id":"662","file":[{"file_size":1844107,"content_type":"application/pdf","creator":"system","access_level":"open_access","file_name":"IST-2016-662-v1+1_ncomms10333.pdf","checksum":"ef147bcbb8bd37e9079cf3ce06f5815d","date_created":"2018-12-12T10:13:52Z","date_updated":"2020-07-14T12:44:44Z","relation":"main_file","file_id":"5039"}],"oa_version":"Published Version","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1332","status":"public","title":"Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments","ddc":["570","579"],"intvolume":" 7","day":"20","has_accepted_license":"1","scopus_import":1,"date_published":"2016-01-20T00:00:00Z","publication":"Nature Communications","citation":{"ama":"Chait RP, Palmer A, Yelin I, Kishony R. Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. 2016;7. doi:10.1038/ncomms10333","ista":"Chait RP, Palmer A, Yelin I, Kishony R. 2016. Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. 7, 10333.","apa":"Chait, R. P., Palmer, A., Yelin, I., & Kishony, R. (2016). Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms10333","ieee":"R. P. Chait, A. Palmer, I. Yelin, and R. Kishony, “Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments,” Nature Communications, vol. 7. Nature Publishing Group, 2016.","mla":"Chait, Remy P., et al. “Pervasive Selection for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.” Nature Communications, vol. 7, 10333, Nature Publishing Group, 2016, doi:10.1038/ncomms10333.","short":"R.P. Chait, A. Palmer, I. Yelin, R. Kishony, Nature Communications 7 (2016).","chicago":"Chait, Remy P, Adam Palmer, Idan Yelin, and Roy Kishony. “Pervasive Selection for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms10333."},"file_date_updated":"2020-07-14T12:44:44Z","publist_id":"5936","article_number":"10333","author":[{"orcid":"0000-0003-0876-3187","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","last_name":"Chait","first_name":"Remy P","full_name":"Chait, Remy P"},{"last_name":"Palmer","first_name":"Adam","full_name":"Palmer, Adam"},{"full_name":"Yelin, Idan","last_name":"Yelin","first_name":"Idan"},{"full_name":"Kishony, Roy","last_name":"Kishony","first_name":"Roy"}],"date_created":"2018-12-11T11:51:25Z","date_updated":"2021-01-12T06:49:57Z","volume":7,"year":"2016","acknowledgement":"This work was partially supported by US National Institutes of Health grant R01-GM081617, Israeli Centers of Research Excellence I-CORE Program ISF Grant No. 152/11, and the European Research Council FP7 ERC Grant 281891.","publication_status":"published","publisher":"Nature Publishing Group","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"month":"01","doi":"10.1038/ncomms10333","language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"quality_controlled":"1"},{"day":"09","month":"09","scopus_import":1,"language":[{"iso":"eng"}],"date_published":"2016-09-09T00:00:00Z","doi":"10.1126/science.aag0822","quality_controlled":"1","page":"1147 - 1151","publication":"Science","citation":{"chicago":"Baym, Michael, Tami Lieberman, Eric Kelsic, Remy P Chait, Rotem Gross, Idan Yelin, and Roy Kishony. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.” Science. American Association for the Advancement of Science, 2016. https://doi.org/10.1126/science.aag0822.","mla":"Baym, Michael, et al. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.” Science, vol. 353, no. 6304, American Association for the Advancement of Science, 2016, pp. 1147–51, doi:10.1126/science.aag0822.","short":"M. Baym, T. Lieberman, E. Kelsic, R.P. Chait, R. Gross, I. Yelin, R. Kishony, Science 353 (2016) 1147–1151.","ista":"Baym M, Lieberman T, Kelsic E, Chait RP, Gross R, Yelin I, Kishony R. 2016. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 353(6304), 1147–1151.","ieee":"M. Baym et al., “Spatiotemporal microbial evolution on antibiotic landscapes,” Science, vol. 353, no. 6304. American Association for the Advancement of Science, pp. 1147–1151, 2016.","apa":"Baym, M., Lieberman, T., Kelsic, E., Chait, R. P., Gross, R., Yelin, I., & Kishony, R. (2016). Spatiotemporal microbial evolution on antibiotic landscapes. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aag0822","ama":"Baym M, Lieberman T, Kelsic E, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016;353(6304):1147-1151. doi:10.1126/science.aag0822"},"oa":1,"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5534434/"}],"abstract":[{"text":"A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front.While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front,we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behindmore sensitive lineages.TheMEGA-plate provides a versatile platformfor studying microbial adaption and directly visualizing evolutionary dynamics.","lang":"eng"}],"issue":"6304","publist_id":"5911","type":"journal_article","date_created":"2018-12-11T11:51:29Z","date_updated":"2021-01-12T06:50:01Z","oa_version":"Preprint","volume":353,"author":[{"last_name":"Baym","first_name":"Michael","full_name":"Baym, Michael"},{"full_name":"Lieberman, Tami","last_name":"Lieberman","first_name":"Tami"},{"last_name":"Kelsic","first_name":"Eric","full_name":"Kelsic, Eric"},{"full_name":"Chait, Remy P","last_name":"Chait","first_name":"Remy P","orcid":"0000-0003-0876-3187","id":"3464AE84-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Rotem","last_name":"Gross","full_name":"Gross, Rotem"},{"first_name":"Idan","last_name":"Yelin","full_name":"Yelin, Idan"},{"first_name":"Roy","last_name":"Kishony","full_name":"Kishony, Roy"}],"publication_status":"published","title":"Spatiotemporal microbial evolution on antibiotic landscapes","status":"public","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"American Association for the Advancement of Science","intvolume":" 353","_id":"1342","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","year":"2016"},{"day":"27","scopus_import":1,"date_published":"2016-05-27T00:00:00Z","publication":"Physical Biology","citation":{"short":"D. De Martino, F. Capuani, A. De Martino, Physical Biology 13 (2016).","mla":"De Martino, Daniele, et al. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology, vol. 13, no. 3, 036005, IOP Publishing Ltd., 2016, doi:10.1088/1478-3975/13/3/036005.","chicago":"De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/3/036005.","ama":"De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005","ieee":"D. De Martino, F. Capuani, and A. De Martino, “Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli,” Physical Biology, vol. 13, no. 3. IOP Publishing Ltd., 2016.","apa":"De Martino, D., Capuani, F., & De Martino, A. (2016). Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/3/036005","ista":"De Martino D, Capuani F, De Martino A. 2016. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 13(3), 036005."},"abstract":[{"text":"The solution space of genome-scale models of cellular metabolism provides a map between physically\r\nviable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the\r\ncorresponding growth rates. By sampling the solution space of E. coliʼs metabolic network, we show\r\nthat empirical growth rate distributions recently obtained in experiments at single-cell resolution can\r\nbe explained in terms of a trade-off between the higher fitness of fast-growing phenotypes and the\r\nhigher entropy of slow-growing ones. Based on this, we propose a minimal model for the evolution of\r\na large bacterial population that captures this trade-off. The scaling relationships observed in\r\nexperiments encode, in such frameworks, for the same distance from the maximum achievable growth\r\nrate, the same degree of growth rate maximization, and/or the same rate of phenotypic change. Being\r\ngrounded on genome-scale metabolic network reconstructions, these results allow for multiple\r\nimplications and extensions in spite of the underlying conceptual simplicity.","lang":"eng"}],"issue":"3","type":"journal_article","oa_version":"Preprint","_id":"1394","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","status":"public","title":"Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli","intvolume":" 13","month":"05","doi":"10.1088/1478-3975/13/3/036005","language":[{"iso":"eng"}],"oa":1,"main_file_link":[{"url":"https://arxiv.org/abs/1601.03243","open_access":"1"}],"quality_controlled":"1","project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"publist_id":"5815","ec_funded":1,"article_number":"036005","author":[{"id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","first_name":"Daniele","last_name":"De Martino","full_name":"De Martino, Daniele"},{"full_name":"Capuani, Fabrizio","first_name":"Fabrizio","last_name":"Capuani"},{"last_name":"De Martino","first_name":"Andrea","full_name":"De Martino, Andrea"}],"date_created":"2018-12-11T11:51:46Z","date_updated":"2021-01-12T06:50:23Z","volume":13,"acknowledgement":"The research leading to these results has received funding from the from the Marie\r\nCurie Action ITN NETADIS, grant agreement no. 290038.","year":"2016","publication_status":"published","publisher":"IOP Publishing Ltd.","department":[{"_id":"GaTk"}]},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1420","title":"A general approximation for the dynamics of quantitative traits","status":"public","intvolume":" 202","oa_version":"Preprint","type":"journal_article","abstract":[{"lang":"eng","text":"Selection, mutation, and random drift affect the dynamics of allele frequencies and consequently of quantitative traits. While the macroscopic dynamics of quantitative traits can be measured, the underlying allele frequencies are typically unobserved. Can we understand how the macroscopic observables evolve without following these microscopic processes? This problem has been studied previously by analogy with statistical mechanics: the allele frequency distribution at each time point is approximated by the stationary form, which maximizes entropy. We explore the limitations of this method when mutation is small (4Nμ < 1) so that populations are typically close to fixation, and we extend the theory in this regime to account for changes in mutation strength. We consider a single diallelic locus either under directional selection or with overdominance and then generalize to multiple unlinked biallelic loci with unequal effects. We find that the maximum-entropy approximation is remarkably accurate, even when mutation and selection change rapidly. "}],"issue":"4","publication":"Genetics","citation":{"ista":"Bodova K, Tkačik G, Barton NH. 2016. A general approximation for the dynamics of quantitative traits. Genetics. 202(4), 1523–1548.","ieee":"K. Bodova, G. Tkačik, and N. H. Barton, “A general approximation for the dynamics of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of America, pp. 1523–1548, 2016.","apa":"Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation for the dynamics of quantitative traits. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.184127","ama":"Bodova K, Tkačik G, Barton NH. A general approximation for the dynamics of quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127","chicago":"Bodova, Katarina, Gašper Tkačik, and Nicholas H Barton. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.184127.","mla":"Bodova, Katarina, et al. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics, vol. 202, no. 4, Genetics Society of America, 2016, pp. 1523–48, doi:10.1534/genetics.115.184127.","short":"K. Bodova, G. Tkačik, N.H. Barton, Genetics 202 (2016) 1523–1548."},"page":"1523 - 1548","date_published":"2016-04-06T00:00:00Z","scopus_import":"1","day":"06","article_processing_charge":"No","year":"2016","publication_status":"published","publisher":"Genetics Society of America","department":[{"_id":"GaTk"},{"_id":"NiBa"}],"author":[{"full_name":"Bod'ová, Katarína","last_name":"Bod'ová","first_name":"Katarína","orcid":"0000-0002-7214-0171","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik"},{"last_name":"Barton","first_name":"Nicholas H","orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H"}],"date_updated":"2022-08-01T10:49:55Z","date_created":"2018-12-11T11:51:55Z","volume":202,"publist_id":"5787","ec_funded":1,"external_id":{"arxiv":["1510.08344"]},"main_file_link":[{"url":"http://arxiv.org/abs/1510.08344","open_access":"1"}],"oa":1,"quality_controlled":"1","project":[{"grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7"},{"grant_number":"RGP0065/2012","_id":"255008E4-B435-11E9-9278-68D0E5697425","name":"Information processing and computation in fish groups"}],"doi":"10.1534/genetics.115.184127","language":[{"iso":"eng"}],"month":"04"},{"month":"01","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1505.04613"}],"oa":1,"language":[{"iso":"eng"}],"doi":"10.1088/1478-3975/13/1/016003","article_number":"016003","ec_funded":1,"publist_id":"5702","publisher":"IOP Publishing Ltd.","department":[{"_id":"GaTk"}],"publication_status":"published","year":"2016","volume":13,"date_created":"2018-12-11T11:52:18Z","date_updated":"2021-01-12T06:51:04Z","author":[{"orcid":"0000-0002-5214-4706","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","last_name":"De Martino","first_name":"Daniele","full_name":"De Martino, Daniele"}],"scopus_import":1,"day":"29","citation":{"ama":"De Martino D. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 2016;13(1). doi:10.1088/1478-3975/13/1/016003","ieee":"D. De Martino, “Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis,” Physical Biology, vol. 13, no. 1. IOP Publishing Ltd., 2016.","apa":"De Martino, D. (2016). Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/1/016003","ista":"De Martino D. 2016. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 13(1), 016003.","short":"D. De Martino, Physical Biology 13 (2016).","mla":"De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology, vol. 13, no. 1, 016003, IOP Publishing Ltd., 2016, doi:10.1088/1478-3975/13/1/016003.","chicago":"De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/1/016003."},"publication":"Physical Biology","date_published":"2016-01-29T00:00:00Z","type":"journal_article","issue":"1","abstract":[{"text":"In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism.","lang":"eng"}],"intvolume":" 13","status":"public","title":"Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1485","oa_version":"Preprint"},{"oa_version":"None","intvolume":" 149","status":"public","title":"Adaptive moment closure for parameter inference of biochemical reaction networks","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1148","abstract":[{"text":"Continuous-time Markov chain (CTMC) models have become a central tool for understanding the dynamics of complex reaction networks and the importance of stochasticity in the underlying biochemical processes. When such models are employed to answer questions in applications, in order to ensure that the model provides a sufficiently accurate representation of the real system, it is of vital importance that the model parameters are inferred from real measured data. This, however, is often a formidable task and all of the existing methods fail in one case or the other, usually because the underlying CTMC model is high-dimensional and computationally difficult to analyze. The parameter inference methods that tend to scale best in the dimension of the CTMC are based on so-called moment closure approximations. However, there exists a large number of different moment closure approximations and it is typically hard to say a priori which of the approximations is the most suitable for the inference procedure. Here, we propose a moment-based parameter inference method that automatically chooses the most appropriate moment closure method. Accordingly, contrary to existing methods, the user is not required to be experienced in moment closure techniques. In addition to that, our method adaptively changes the approximation during the parameter inference to ensure that always the best approximation is used, even in cases where different approximations are best in different regions of the parameter space. © 2016 Elsevier Ireland Ltd","lang":"eng"}],"type":"journal_article","date_published":"2016-11-01T00:00:00Z","page":"15 - 25","citation":{"ama":"Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. 2016;149:15-25. doi:10.1016/j.biosystems.2016.07.005","ista":"Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. 2016. Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. 149, 15–25.","ieee":"C. Schilling, S. Bogomolov, T. A. Henzinger, A. Podelski, and J. Ruess, “Adaptive moment closure for parameter inference of biochemical reaction networks,” Biosystems, vol. 149. Elsevier, pp. 15–25, 2016.","apa":"Schilling, C., Bogomolov, S., Henzinger, T. A., Podelski, A., & Ruess, J. (2016). Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. Elsevier. https://doi.org/10.1016/j.biosystems.2016.07.005","mla":"Schilling, Christian, et al. “Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks.” Biosystems, vol. 149, Elsevier, 2016, pp. 15–25, doi:10.1016/j.biosystems.2016.07.005.","short":"C. Schilling, S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, Biosystems 149 (2016) 15–25.","chicago":"Schilling, Christian, Sergiy Bogomolov, Thomas A Henzinger, Andreas Podelski, and Jakob Ruess. “Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks.” Biosystems. Elsevier, 2016. https://doi.org/10.1016/j.biosystems.2016.07.005."},"publication":"Biosystems","day":"01","scopus_import":1,"volume":149,"date_created":"2018-12-11T11:50:24Z","date_updated":"2023-02-23T10:08:46Z","related_material":{"record":[{"id":"1658","relation":"earlier_version","status":"public"}]},"author":[{"full_name":"Schilling, Christian","first_name":"Christian","last_name":"Schilling"},{"id":"369D9A44-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-0686-0365","first_name":"Sergiy","last_name":"Bogomolov","full_name":"Bogomolov, Sergiy"},{"full_name":"Henzinger, Thomas A","last_name":"Henzinger","first_name":"Thomas A","orcid":"0000−0002−2985−7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Andreas","last_name":"Podelski","full_name":"Podelski, Andreas"},{"full_name":"Ruess, Jakob","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1615-3282","first_name":"Jakob","last_name":"Ruess"}],"department":[{"_id":"ToHe"},{"_id":"GaTk"}],"publisher":"Elsevier","publication_status":"published","year":"2016","acknowledgement":"This work is based on the CMSB 2015 paper “Adaptive moment closure for parameter inference of biochemical reaction networks” (Bogomolov et al., 2015). The work was partly supported by the German Research Foundation (DFG) as part of the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS1), by the European Research Council (ERC) under grant 267989 (QUAREM) and by the Austrian Science Fund (FWF) under grants S11402-N23 (RiSE) and Z211-N23 (Wittgenstein Award). J.R. acknowledges support from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. 291734.","ec_funded":1,"publist_id":"6210","language":[{"iso":"eng"}],"doi":"10.1016/j.biosystems.2016.07.005","project":[{"call_identifier":"FP7","name":"Quantitative Reactive Modeling","grant_number":"267989","_id":"25EE3708-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","name":"Rigorous Systems Engineering","grant_number":"S 11407_N23","_id":"25832EC2-B435-11E9-9278-68D0E5697425"},{"grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","name":"The Wittgenstein Prize","call_identifier":"FWF"},{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"quality_controlled":"1","month":"11"},{"file":[{"file_size":678670,"content_type":"application/pdf","creator":"cziletti","file_name":"2016_ProcALIFE_Martius.pdf","access_level":"open_access","date_updated":"2020-07-14T12:48:09Z","date_created":"2020-07-06T12:59:09Z","checksum":"cff63e7a4b8ac466ba51a9c84153a940","relation":"main_file","file_id":"8096"}],"oa_version":"Published Version","user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","_id":"8094","intvolume":" 28","ddc":["610"],"status":"public","title":"Self-organized control of an tendon driven arm by differential extrinsic plasticity","abstract":[{"text":"With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. The idea is that the controller controls the world---the body plus its environment---as reliably as possible. This paper focuses on new lines of self-organization for developmental robotics. We apply the recently developed differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object's internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently discovers how to rotate it. In this way, the robot discovers affordances of objects its body is interacting with.","lang":"eng"}],"type":"conference","date_published":"2016-09-01T00:00:00Z","citation":{"ieee":"G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Self-organized control of an tendon driven arm by differential extrinsic plasticity,” in Proceedings of the Artificial Life Conference 2016, Cancun, Mexico, 2016, vol. 28, pp. 142–143.","apa":"Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Self-organized control of an tendon driven arm by differential extrinsic plasticity. In Proceedings of the Artificial Life Conference 2016 (Vol. 28, pp. 142–143). Cancun, Mexico: MIT Press. https://doi.org/10.7551/978-0-262-33936-0-ch029","ista":"Martius GS, Hostettler R, Knoll A, Der R. 2016. Self-organized control of an tendon driven arm by differential extrinsic plasticity. Proceedings of the Artificial Life Conference 2016. ALIFE 2016: 15th International Conference on the Synthesis and Simulation of Living Systems vol. 28, 142–143.","ama":"Martius GS, Hostettler R, Knoll A, Der R. Self-organized control of an tendon driven arm by differential extrinsic plasticity. In: Proceedings of the Artificial Life Conference 2016. Vol 28. MIT Press; 2016:142-143. doi:10.7551/978-0-262-33936-0-ch029","chicago":"Martius, Georg S, Rafael Hostettler, Alois Knoll, and Ralf Der. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.” In Proceedings of the Artificial Life Conference 2016, 28:142–43. MIT Press, 2016. https://doi.org/10.7551/978-0-262-33936-0-ch029.","short":"G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, Proceedings of the Artificial Life Conference 2016, MIT Press, 2016, pp. 142–143.","mla":"Martius, Georg S., et al. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.” Proceedings of the Artificial Life Conference 2016, vol. 28, MIT Press, 2016, pp. 142–43, doi:10.7551/978-0-262-33936-0-ch029."},"publication":"Proceedings of the Artificial Life Conference 2016","page":"142-143","article_processing_charge":"No","has_accepted_license":"1","day":"01","scopus_import":1,"author":[{"full_name":"Martius, Georg S","first_name":"Georg S","last_name":"Martius","id":"3A276B68-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Hostettler, Rafael","first_name":"Rafael","last_name":"Hostettler"},{"full_name":"Knoll, Alois","last_name":"Knoll","first_name":"Alois"},{"last_name":"Der","first_name":"Ralf","full_name":"Der, Ralf"}],"volume":28,"date_updated":"2021-01-12T08:16:53Z","date_created":"2020-07-05T22:00:47Z","year":"2016","publisher":"MIT Press","department":[{"_id":"ChLa"},{"_id":"GaTk"}],"publication_status":"published","ec_funded":1,"file_date_updated":"2020-07-14T12:48:09Z","doi":"10.7551/978-0-262-33936-0-ch029","conference":{"end_date":"2016-07-08","location":"Cancun, Mexico","start_date":"2016-07-04","name":"ALIFE 2016: 15th International Conference on the Synthesis and Simulation of Living Systems"},"language":[{"iso":"eng"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","publication_identifier":{"isbn":["9780262339360"]},"month":"09"},{"month":"11","project":[{"call_identifier":"FWF","name":"Sensitivity to higher-order statistics in natural scenes","grant_number":"P 25651-N26","_id":"254D1A94-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"language":[{"iso":"eng"}],"doi":"10.1371/journal.pcbi.1005148","article_number":"e1005855","publist_id":"6153","file_date_updated":"2020-07-14T12:44:38Z","publisher":"Public Library of Science","department":[{"_id":"GaTk"}],"publication_status":"published","acknowledgement":"JSP was supported by a C.V. Starr Fellowship from the Starr Foundation (http://www.starrfoundation.org/). GT was supported by Austrian Research Foundation (https://www.fwf.ac.at/en/) grant FWF P25651. MJB received support from National Eye Institute (https://nei.nih.gov/) grant EY 14196 and from the National Science Foundation grant 1504977. The authors thank Cristina Savin and Vicent Botella-Soler for helpful comments on the manuscript.","year":"2016","volume":12,"date_created":"2018-12-11T11:50:40Z","date_updated":"2023-02-23T14:05:40Z","related_material":{"record":[{"status":"public","relation":"research_data","id":"9709"}]},"author":[{"first_name":"Jason","last_name":"Prentice","full_name":"Prentice, Jason"},{"last_name":"Marre","first_name":"Olivier","full_name":"Marre, Olivier"},{"last_name":"Ioffe","first_name":"Mark","full_name":"Ioffe, Mark"},{"last_name":"Loback","first_name":"Adrianna","full_name":"Loback, Adrianna"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik","full_name":"Tkacik, Gasper"},{"full_name":"Berry, Michael","first_name":"Michael","last_name":"Berry"}],"scopus_import":1,"has_accepted_license":"1","day":"17","citation":{"ama":"Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. Error-robust modes of the retinal population code. PLoS Computational Biology. 2016;12(11). doi:10.1371/journal.pcbi.1005148","ieee":"J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, and M. Berry, “Error-robust modes of the retinal population code,” PLoS Computational Biology, vol. 12, no. 11. Public Library of Science, 2016.","apa":"Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M. (2016). Error-robust modes of the retinal population code. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005148","ista":"Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. 2016. Error-robust modes of the retinal population code. PLoS Computational Biology. 12(11), e1005855.","short":"J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, M. Berry, PLoS Computational Biology 12 (2016).","mla":"Prentice, Jason, et al. “Error-Robust Modes of the Retinal Population Code.” PLoS Computational Biology, vol. 12, no. 11, e1005855, Public Library of Science, 2016, doi:10.1371/journal.pcbi.1005148.","chicago":"Prentice, Jason, Olivier Marre, Mark Ioffe, Adrianna Loback, Gašper Tkačik, and Michael Berry. “Error-Robust Modes of the Retinal Population Code.” PLoS Computational Biology. Public Library of Science, 2016. https://doi.org/10.1371/journal.pcbi.1005148."},"publication":"PLoS Computational Biology","date_published":"2016-11-17T00:00:00Z","type":"journal_article","issue":"11","abstract":[{"lang":"eng","text":"Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells’ collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina."}],"intvolume":" 12","ddc":["570"],"title":"Error-robust modes of the retinal population code","status":"public","_id":"1197","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","file":[{"relation":"main_file","file_id":"5884","date_created":"2019-01-25T10:35:00Z","date_updated":"2020-07-14T12:44:38Z","checksum":"47b08cbd4dbf32b25ba161f5f4b262cc","file_name":"2016_PLOS_Prentice.pdf","access_level":"open_access","file_size":4492021,"content_type":"application/pdf","creator":"kschuh"}]},{"abstract":[{"text":"Experience constantly shapes neural circuits through a variety of plasticity mechanisms. While the functional roles of some plasticity mechanisms are well-understood, it remains unclear how changes in neural excitability contribute to learning. Here, we develop a normative interpretation of intrinsic plasticity (IP) as a key component of unsupervised learning. We introduce a novel generative mixture model that accounts for the class-specific statistics of stimulus intensities, and we derive a neural circuit that learns the input classes and their intensities. We will analytically show that inference and learning for our generative model can be achieved by a neural circuit with intensity-sensitive neurons equipped with a specific form of IP. Numerical experiments verify our analytical derivations and show robust behavior for artificial and natural stimuli. Our results link IP to non-trivial input statistics, in particular the statistics of stimulus intensities for classes to which a neuron is sensitive. More generally, our work paves the way toward new classification algorithms that are robust to intensity variations.","lang":"eng"}],"type":"conference","alternative_title":["Advances in Neural Information Processing Systems"],"oa_version":"None","_id":"948","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","status":"public","title":"Neurons equipped with intrinsic plasticity learn stimulus intensity statistics","intvolume":" 29","day":"01","scopus_import":1,"date_published":"2016-01-01T00:00:00Z","citation":{"ista":"Monk T, Savin C, Lücke J. 2016. Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 4285–4293.","apa":"Monk, T., Savin, C., & Lücke, J. (2016). Neurons equipped with intrinsic plasticity learn stimulus intensity statistics (Vol. 29, pp. 4285–4293). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine: Neural Information Processing Systems.","ieee":"T. Monk, C. Savin, and J. Lücke, “Neurons equipped with intrinsic plasticity learn stimulus intensity statistics,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine, 2016, vol. 29, pp. 4285–4293.","ama":"Monk T, Savin C, Lücke J. Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. In: Vol 29. Neural Information Processing Systems; 2016:4285-4293.","chicago":"Monk, Travis, Cristina Savin, and Jörg Lücke. “Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics,” 29:4285–93. Neural Information Processing Systems, 2016.","mla":"Monk, Travis, et al. Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics. Vol. 29, Neural Information Processing Systems, 2016, pp. 4285–93.","short":"T. Monk, C. Savin, J. Lücke, in:, Neural Information Processing Systems, 2016, pp. 4285–4293."},"page":"4285 - 4293","ec_funded":1,"publist_id":"6469","author":[{"full_name":"Monk, Travis","first_name":"Travis","last_name":"Monk"},{"full_name":"Savin, Cristina","first_name":"Cristina","last_name":"Savin","id":"3933349E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Jörg","last_name":"Lücke","full_name":"Lücke, Jörg"}],"date_updated":"2021-01-12T08:22:08Z","date_created":"2018-12-11T11:49:21Z","volume":29,"year":"2016","acknowledgement":"DFG Cluster of Excellence EXC 1077/1 (Hearing4all) and LU 1196/5-1 (JL and TM), People Programme (Marie Curie Actions) FP7/2007-2013 grant agreement no. 291734 (CS)","publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Neural Information Processing Systems","month":"01","conference":{"end_date":"2016-12-10","location":"Barcelona, Spaine","start_date":"2016-12-05","name":"NIPS: Neural Information Processing Systems"},"language":[{"iso":"eng"}],"main_file_link":[{"url":"https://papers.nips.cc/paper/6582-neurons-equipped-with-intrinsic-plasticity-learn-stimulus-intensity-statistics"}],"quality_controlled":"1","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}]}]