[{"oa_version":"Published Version","title":"Eukaryotic gene regulation at equilibrium, or non?","author":[{"first_name":"Benjamin","full_name":"Zoller, Benjamin","last_name":"Zoller"},{"full_name":"Gregor, Thomas","last_name":"Gregor","first_name":"Thomas"},{"last_name":"Tkačik","full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"1","first_name":"Gašper"}],"scopus_import":"1","day":"01","article_type":"original","date_created":"2023-01-12T12:08:51Z","volume":31,"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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"intvolume":"        31","abstract":[{"text":"Models of transcriptional regulation that assume equilibrium binding of transcription factors have been less successful at predicting gene expression from sequence in eukaryotes than in bacteria. This could be due to the non-equilibrium nature of eukaryotic regulation. Unfortunately, the space of possible non-equilibrium mechanisms is vast and predominantly uninteresting. The key question is therefore how this space can be navigated efficiently, to focus on mechanisms and models that are biologically relevant. In this review, we advocate for the normative role of theory—theory that prescribes rather than just describes—in providing such a focus. Theory should expand its remit beyond inferring mechanistic models from data, towards identifying non-equilibrium gene regulatory schemes that may have been evolutionarily selected, despite their energy consumption, because they are precise, reliable, fast, or otherwise outperform regulation at equilibrium. We illustrate our reasoning by toy examples for which we provide simulation code.","lang":"eng"}],"has_accepted_license":"1","publication_identifier":{"issn":["2452-3100"]},"publication_status":"published","file_date_updated":"2023-01-24T12:14:10Z","month":"09","article_number":"100435","file":[{"relation":"main_file","checksum":"97ef01e0cc60cdc84f45640a0f248fb0","success":1,"file_name":"2022_CurrentBiology_Zoller.pdf","access_level":"open_access","content_type":"application/pdf","file_id":"12362","file_size":2214944,"date_created":"2023-01-24T12:14:10Z","date_updated":"2023-01-24T12:14:10Z","creator":"dernst"}],"department":[{"_id":"GaTk"}],"language":[{"iso":"eng"}],"oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"9","citation":{"ieee":"B. Zoller, T. Gregor, and G. Tkačik, “Eukaryotic gene regulation at equilibrium, or non?,” <i>Current Opinion in Systems Biology</i>, vol. 31, no. 9. Elsevier, 2022.","short":"B. Zoller, T. Gregor, G. Tkačik, Current Opinion in Systems Biology 31 (2022).","ama":"Zoller B, Gregor T, Tkačik G. Eukaryotic gene regulation at equilibrium, or non? <i>Current Opinion in Systems Biology</i>. 2022;31(9). doi:<a href=\"https://doi.org/10.1016/j.coisb.2022.100435\">10.1016/j.coisb.2022.100435</a>","apa":"Zoller, B., Gregor, T., &#38; Tkačik, G. (2022). Eukaryotic gene regulation at equilibrium, or non? <i>Current Opinion in Systems Biology</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.coisb.2022.100435\">https://doi.org/10.1016/j.coisb.2022.100435</a>","mla":"Zoller, Benjamin, et al. “Eukaryotic Gene Regulation at Equilibrium, or Non?” <i>Current Opinion in Systems Biology</i>, vol. 31, no. 9, 100435, Elsevier, 2022, doi:<a href=\"https://doi.org/10.1016/j.coisb.2022.100435\">10.1016/j.coisb.2022.100435</a>.","ista":"Zoller B, Gregor T, Tkačik G. 2022. Eukaryotic gene regulation at equilibrium, or non? Current Opinion in Systems Biology. 31(9), 100435.","chicago":"Zoller, Benjamin, Thomas Gregor, and Gašper Tkačik. “Eukaryotic Gene Regulation at Equilibrium, or Non?” <i>Current Opinion in Systems Biology</i>. Elsevier, 2022. <a href=\"https://doi.org/10.1016/j.coisb.2022.100435\">https://doi.org/10.1016/j.coisb.2022.100435</a>."},"publisher":"Elsevier","doi":"10.1016/j.coisb.2022.100435","article_processing_charge":"Yes (via OA deal)","type":"journal_article","date_updated":"2023-02-13T09:20:34Z","_id":"12156","ddc":["570"],"quality_controlled":"1","year":"2022","keyword":["Applied Mathematics","Computer Science Applications","Drug Discovery","General Biochemistry","Genetics and Molecular Biology","Modeling and Simulation"],"project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","call_identifier":"FWF"}],"publication":"Current Opinion in Systems Biology","status":"public","acknowledgement":"This work was supported through the Center for the Physics of Biological Function (PHYe1734030) and by National Institutes of Health Grants R01GM097275 and U01DK127429 (TG). GT acknowledges the support of the Austrian Science Fund grant FWF P28844 and the Human Frontiers Science Program. ","date_published":"2022-09-01T00:00:00Z"},{"doi":"10.1371/journal.pcbi.1008529","article_processing_charge":"Yes","publisher":"Public Library of Science","date_updated":"2024-02-21T12:41:41Z","_id":"8997","type":"journal_article","ddc":["570"],"quality_controlled":"1","year":"2021","isi":1,"external_id":{"isi":["000608045000010"]},"related_material":{"record":[{"id":"7673","status":"public","relation":"earlier_version"},{"id":"8930","status":"public","relation":"research_data"}]},"keyword":["Modelling and Simulation","Genetics","Molecular Biology","Antibiotics","Drug interactions"],"project":[{"_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"P27201-B22","name":"Revealing the mechanisms underlying drug interactions"},{"_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27"}],"publication":"PLOS Computational Biology","status":"public","date_published":"2021-01-07T00:00:00Z","acknowledgement":"This work was supported in part by Tum stipend of Knafelj foundation (to B.K.), Austrian Science Fund (FWF) standalone grants P 27201-B22 (to T.B.) and P 28844(to G.T.), HFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation (DFG) individual grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG) Collaborative Research Centre (SFB) 1310 (to T.B.). ","author":[{"orcid":"0000-0001-6041-254X","first_name":"Bor","last_name":"Kavcic","full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-6699-1455","first_name":"Gašper","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper"},{"first_name":"Tobias","orcid":"0000-0003-4398-476X","last_name":"Bollenbach","full_name":"Bollenbach, Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"day":"07","oa_version":"Published Version","title":"Minimal biophysical model of combined antibiotic action","volume":17,"article_type":"original","date_created":"2021-01-08T07:16:18Z","has_accepted_license":"1","abstract":[{"lang":"eng","text":"Phenomenological relations such as Ohm’s or Fourier’s law have a venerable history in physics but are still scarce in biology. This situation restrains predictive theory. Here, we build on bacterial “growth laws,” which capture physiological feedback between translation and cell growth, to construct a minimal biophysical model for the combined action of ribosome-targeting antibiotics. Our model predicts drug interactions like antagonism or synergy solely from responses to individual drugs. We provide analytical results for limiting cases, which agree well with numerical results. We systematically refine the model by including direct physical interactions of different antibiotics on the ribosome. In a limiting case, our model provides a mechanistic underpinning for recent predictions of higher-order interactions that were derived using entropy maximization. We further refine the model to include the effects of antibiotics that mimic starvation and the presence of resistance genes. We describe the impact of a starvation-mimicking antibiotic on drug interactions analytically and verify it experimentally. Our extended model suggests a change in the type of drug interaction that depends on the strength of resistance, which challenges established rescaling paradigms. We experimentally show that the presence of unregulated resistance genes can lead to altered drug interaction, which agrees with the prediction of the model. While minimal, the model is readily adaptable and opens the door to predicting interactions of second and higher-order in a broad range of biological systems."}],"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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"intvolume":"        17","publication_identifier":{"issn":["1553-7358"]},"publication_status":"published","file_date_updated":"2021-02-04T12:30:48Z","month":"01","department":[{"_id":"GaTk"}],"article_number":"e1008529","file":[{"relation":"main_file","checksum":"e29f2b42651bef8e034781de8781ffac","success":1,"file_name":"2021_PlosComBio_Kavcic.pdf","access_level":"open_access","content_type":"application/pdf","file_id":"9092","file_size":3690053,"date_created":"2021-02-04T12:30:48Z","date_updated":"2021-02-04T12:30:48Z","creator":"dernst"}],"oa":1,"language":[{"iso":"eng"}],"citation":{"ista":"Kavcic B, Tkačik G, Bollenbach MT. 2021. Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. 17, e1008529.","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Minimal Biophysical Model of Combined Antibiotic Action.” <i>PLOS Computational Biology</i>. Public Library of Science, 2021. <a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">https://doi.org/10.1371/journal.pcbi.1008529</a>.","apa":"Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2021). Minimal biophysical model of combined antibiotic action. <i>PLOS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">https://doi.org/10.1371/journal.pcbi.1008529</a>","mla":"Kavcic, Bor, et al. “Minimal Biophysical Model of Combined Antibiotic Action.” <i>PLOS Computational Biology</i>, vol. 17, e1008529, Public Library of Science, 2021, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">10.1371/journal.pcbi.1008529</a>.","ama":"Kavcic B, Tkačik G, Bollenbach MT. Minimal biophysical model of combined antibiotic action. <i>PLOS Computational Biology</i>. 2021;17. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">10.1371/journal.pcbi.1008529</a>","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Minimal biophysical model of combined antibiotic action,” <i>PLOS Computational Biology</i>, vol. 17. Public Library of Science, 2021.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, PLOS Computational Biology 17 (2021)."},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8"},{"date_updated":"2023-08-07T13:57:30Z","_id":"9226","type":"journal_article","doi":"10.1242/dev.176065","article_processing_charge":"No","publisher":"The Company of Biologists","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1242/dev.176065"}],"quality_controlled":"1","isi":1,"year":"2021","external_id":{"pmid":["33526425"],"isi":["000613906000007"]},"pmid":1,"date_published":"2021-02-01T00:00:00Z","acknowledgement":"This work was supported in part by the National Science Foundation, through the Center for the Physics of Biological Function (PHY-1734030), by the National Institutes of Health (R01GM097275) and by the Fonds zur Förderung der wissenschaftlichen Forschung (FWF P28844). Deposited in PMC for release after 12 months.","project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"status":"public","publication":"Development","volume":148,"article_type":"original","date_created":"2021-03-07T23:01:25Z","author":[{"first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","last_name":"Tkačik"},{"full_name":"Gregor, Thomas","last_name":"Gregor","first_name":"Thomas"}],"day":"01","scopus_import":"1","title":"The many bits of positional information","oa_version":"Published Version","publication_identifier":{"eissn":["1477-9129"]},"publication_status":"published","intvolume":"       148","abstract":[{"text":"Half a century after Lewis Wolpert's seminal conceptual advance on how cellular fates distribute in space, we provide a brief historical perspective on how the concept of positional information emerged and influenced the field of developmental biology and beyond. We focus on a modern interpretation of this concept in terms of information theory, largely centered on its application to cell specification in the early Drosophila embryo. We argue that a true physical variable (position) is encoded in local concentrations of patterning molecules, that this mapping is stochastic, and that the processes by which positions and corresponding cell fates are determined based on these concentrations need to take such stochasticity into account. With this approach, we shift the focus from biological mechanisms, molecules, genes and pathways to quantitative systems-level questions: where does positional information reside, how it is transformed and accessed during development, and what fundamental limits it is subject to?","lang":"eng"}],"department":[{"_id":"GaTk"}],"article_number":"dev176065","month":"02","issue":"2","citation":{"ama":"Tkačik G, Gregor T. The many bits of positional information. <i>Development</i>. 2021;148(2). doi:<a href=\"https://doi.org/10.1242/dev.176065\">10.1242/dev.176065</a>","short":"G. Tkačik, T. Gregor, Development 148 (2021).","ieee":"G. Tkačik and T. Gregor, “The many bits of positional information,” <i>Development</i>, vol. 148, no. 2. The Company of Biologists, 2021.","ista":"Tkačik G, Gregor T. 2021. The many bits of positional information. Development. 148(2), dev176065.","chicago":"Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.” <i>Development</i>. The Company of Biologists, 2021. <a href=\"https://doi.org/10.1242/dev.176065\">https://doi.org/10.1242/dev.176065</a>.","mla":"Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.” <i>Development</i>, vol. 148, no. 2, dev176065, The Company of Biologists, 2021, doi:<a href=\"https://doi.org/10.1242/dev.176065\">10.1242/dev.176065</a>.","apa":"Tkačik, G., &#38; Gregor, T. (2021). The many bits of positional information. <i>Development</i>. The Company of Biologists. <a href=\"https://doi.org/10.1242/dev.176065\">https://doi.org/10.1242/dev.176065</a>"},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","oa":1,"language":[{"iso":"eng"}]},{"publication_identifier":{"issn":["2041-1723"]},"publication_status":"published","file_date_updated":"2020-08-17T07:36:57Z","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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"intvolume":"        11","abstract":[{"text":"Antibiotics that interfere with translation, when combined, interact in diverse and difficult-to-predict ways. Here, we explain these interactions by “translation bottlenecks”: points in the translation cycle where antibiotics block ribosomal progression. To elucidate the underlying mechanisms of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using inducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks causes these interactions. We further show that growth laws, combined with drug uptake and binding kinetics, enable the direct prediction of a large fraction of observed interactions, yet fail to predict suppression. However, varying two translation bottlenecks simultaneously supports that dense traffic of ribosomes and competition for translation factors account for the previously unexplained suppression. These results highlight the importance of “continuous epistasis” in bacterial physiology.","lang":"eng"}],"has_accepted_license":"1","article_type":"original","date_created":"2020-08-12T09:13:50Z","volume":11,"title":"Mechanisms of drug interactions between translation-inhibiting antibiotics","oa_version":"Published Version","author":[{"id":"350F91D2-F248-11E8-B48F-1D18A9856A87","full_name":"Kavcic, Bor","last_name":"Kavcic","first_name":"Bor","orcid":"0000-0001-6041-254X"},{"first_name":"Gašper","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik"},{"orcid":"0000-0003-4398-476X","first_name":"Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Tobias"}],"day":"11","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","citation":{"chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.” <i>Nature Communications</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1038/s41467-020-17734-z\">https://doi.org/10.1038/s41467-020-17734-z</a>.","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 11, 4013.","apa":"Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2020). Mechanisms of drug interactions between translation-inhibiting antibiotics. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-020-17734-z\">https://doi.org/10.1038/s41467-020-17734-z</a>","mla":"Kavcic, Bor, et al. “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.” <i>Nature Communications</i>, vol. 11, 4013, Springer Nature, 2020, doi:<a href=\"https://doi.org/10.1038/s41467-020-17734-z\">10.1038/s41467-020-17734-z</a>.","ama":"Kavcic B, Tkačik G, Bollenbach MT. Mechanisms of drug interactions between translation-inhibiting antibiotics. <i>Nature Communications</i>. 2020;11. doi:<a href=\"https://doi.org/10.1038/s41467-020-17734-z\">10.1038/s41467-020-17734-z</a>","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Mechanisms of drug interactions between translation-inhibiting antibiotics,” <i>Nature Communications</i>, vol. 11. Springer Nature, 2020.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, Nature Communications 11 (2020)."},"language":[{"iso":"eng"}],"oa":1,"article_number":"4013","file":[{"success":1,"file_name":"2020_NatureComm_Kavcic.pdf","access_level":"open_access","content_type":"application/pdf","relation":"main_file","checksum":"986bebb308850a55850028d3d2b5b664","date_created":"2020-08-17T07:36:57Z","file_size":1965672,"date_updated":"2020-08-17T07:36:57Z","creator":"dernst","file_id":"8275"}],"department":[{"_id":"GaTk"}],"month":"08","quality_controlled":"1","ddc":["570"],"type":"journal_article","date_updated":"2024-03-25T23:30:05Z","_id":"8250","publisher":"Springer Nature","doi":"10.1038/s41467-020-17734-z","article_processing_charge":"No","acknowledgement":"We thank M. Hennessey-Wesen, I. Tomanek, K. Jain, A. Staron, K. Tomasek, M. Scott,\r\nK.C. Huang, and Z. Gitai for reading the manuscript and constructive comments. B.K. is\r\nindebted to C. Guet for additional guidance and generous support, which rendered this\r\nwork possible. B.K. thanks all members of Guet group for many helpful discussions and\r\nsharing of resources. B.K. additionally acknowledges the tremendous support from A.\r\nAngermayr and K. Mitosch with experimental work. We further thank E. Brown for\r\nhelpful comments regarding lamotrigine, and A. Buskirk for valuable suggestions\r\nregarding the ribosome footprint size. This work was supported in part by Austrian\r\nScience Fund (FWF) standalone grants P 27201-B22 (to T.B.) and P 28844 (to G.T.),\r\nHFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation (DFG)\r\nstandalone grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG)\r\nCollaborative Research Centre (SFB) 1310 (to T.B.). Open access funding provided by\r\nProjekt DEAL.","date_published":"2020-08-11T00:00:00Z","project":[{"name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22","call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"status":"public","publication":"Nature Communications","external_id":{"isi":["000562769300008"]},"related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"8657"}]},"isi":1,"year":"2020"},{"date_updated":"2024-03-25T23:30:05Z","_id":"7673","type":"preprint","date_created":"2020-04-22T08:27:56Z","author":[{"last_name":"Kavcic","full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6041-254X","first_name":"Bor"},{"last_name":"Tkačik","full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper"},{"last_name":"Bollenbach","full_name":"Bollenbach, Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","first_name":"Tobias"}],"doi":"10.1101/2020.04.18.047886","day":"18","article_processing_charge":"No","oa_version":"Preprint","publisher":"Cold Spring Harbor Laboratory","title":"A minimal biophysical model of combined antibiotic action","main_file_link":[{"url":"https://doi.org/10.1101/2020.04.18.047886 ","open_access":"1"}],"publication_status":"published","abstract":[{"lang":"eng","text":"Combining drugs can improve the efficacy of treatments. However, predicting the effect of drug combinations is still challenging. The combined potency of drugs determines the drug interaction, which is classified as synergistic, additive, antagonistic, or suppressive. While probabilistic, non-mechanistic models exist, there is currently no biophysical model that can predict antibiotic interactions. Here, we present a physiologically relevant model of the combined action of antibiotics that inhibit protein synthesis by targeting the ribosome. This model captures the kinetics of antibiotic binding and transport, and uses bacterial growth laws to predict growth in the presence of antibiotic combinations. We find that this biophysical model can produce all drug interaction types except suppression. We show analytically that antibiotics which cannot bind to the ribosome simultaneously generally act as substitutes for one another, leading to additive drug interactions. Previously proposed null expectations for higher-order drug interactions follow as a limiting case of our model. We further extend the model to include the effects of direct physical or allosteric interactions between individual drugs on the ribosome. Notably, such direct interactions profoundly change the combined drug effect, depending on the kinetic parameters of the drugs used. The model makes additional predictions for the effects of resistance genes on drug interactions and for interactions between ribosome-targeting antibiotics and antibiotics with other targets. These findings enhance our understanding of the interplay between drug action and cell physiology and are a key step toward a general framework for predicting drug interactions."}],"department":[{"_id":"GaTk"}],"year":"2020","month":"04","related_material":{"record":[{"relation":"later_version","status":"public","id":"8997"},{"id":"8657","status":"public","relation":"dissertation_contains"}]},"citation":{"ama":"Kavcic B, Tkačik G, Bollenbach MT. A minimal biophysical model of combined antibiotic action. <i>bioRxiv</i>. 2020. doi:<a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “A minimal biophysical model of combined antibiotic action,” <i>bioRxiv</i>. Cold Spring Harbor Laboratory, 2020.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, BioRxiv (2020).","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “A Minimal Biophysical Model of Combined Antibiotic Action.” <i>BioRxiv</i>. Cold Spring Harbor Laboratory, 2020. <a href=\"https://doi.org/10.1101/2020.04.18.047886\">https://doi.org/10.1101/2020.04.18.047886</a>.","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. A minimal biophysical model of combined antibiotic action. bioRxiv, <a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>.","apa":"Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2020). A minimal biophysical model of combined antibiotic action. <i>bioRxiv</i>. Cold Spring Harbor Laboratory. <a href=\"https://doi.org/10.1101/2020.04.18.047886\">https://doi.org/10.1101/2020.04.18.047886</a>","mla":"Kavcic, Bor, et al. “A Minimal Biophysical Model of Combined Antibiotic Action.” <i>BioRxiv</i>, Cold Spring Harbor Laboratory, 2020, doi:<a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>."},"date_published":"2020-04-18T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"project":[{"call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"language":[{"iso":"eng"}],"publication":"bioRxiv","status":"public"},{"status":"public","publication":"PLoS computational biology","project":[{"grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"pmid":1,"date_published":"2019-09-03T00:00:00Z","year":"2019","isi":1,"related_material":{"record":[{"id":"6473","relation":"part_of_dissertation","status":"public"}]},"external_id":{"pmid":["31479447"],"isi":["000489741800021"]},"page":"e1007290","ddc":["570"],"quality_controlled":"1","article_processing_charge":"No","doi":"10.1371/journal.pcbi.1007290","publisher":"Public Library of Science","_id":"6900","date_updated":"2023-09-07T12:55:21Z","type":"journal_article","oa":1,"language":[{"iso":"eng"}],"citation":{"short":"S.A. Cepeda Humerez, J. Ruess, G. Tkačik, PLoS Computational Biology 15 (2019) e1007290.","ieee":"S. A. Cepeda Humerez, J. Ruess, and G. Tkačik, “Estimating information in time-varying signals,” <i>PLoS computational biology</i>, vol. 15, no. 9. Public Library of Science, p. e1007290, 2019.","ama":"Cepeda Humerez SA, Ruess J, Tkačik G. Estimating information in time-varying signals. <i>PLoS computational biology</i>. 2019;15(9):e1007290. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">10.1371/journal.pcbi.1007290</a>","mla":"Cepeda Humerez, Sarah A., et al. “Estimating Information in Time-Varying Signals.” <i>PLoS Computational Biology</i>, vol. 15, no. 9, Public Library of Science, 2019, p. e1007290, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">10.1371/journal.pcbi.1007290</a>.","apa":"Cepeda Humerez, S. A., Ruess, J., &#38; Tkačik, G. (2019). Estimating information in time-varying signals. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">https://doi.org/10.1371/journal.pcbi.1007290</a>","chicago":"Cepeda Humerez, Sarah A, Jakob Ruess, and Gašper Tkačik. “Estimating Information in Time-Varying Signals.” <i>PLoS Computational Biology</i>. Public Library of Science, 2019. <a href=\"https://doi.org/10.1371/journal.pcbi.1007290\">https://doi.org/10.1371/journal.pcbi.1007290</a>.","ista":"Cepeda Humerez SA, Ruess J, Tkačik G. 2019. Estimating information in time-varying signals. PLoS computational biology. 15(9), e1007290."},"issue":"9","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","month":"09","department":[{"_id":"GaTk"}],"file":[{"file_id":"6925","date_updated":"2020-07-14T12:47:44Z","creator":"kschuh","date_created":"2019-10-01T10:53:45Z","file_size":3081855,"checksum":"81bdce1361c9aa8395d6fa635fb6ab47","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_name":"2019_PLoS_Cepeda-Humerez.pdf"}],"has_accepted_license":"1","intvolume":"        15","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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"abstract":[{"text":"Across diverse biological systems—ranging from neural networks to intracellular signaling and genetic regulatory networks—the information about changes in the environment is frequently encoded in the full temporal dynamics of the network nodes. A pressing data-analysis challenge has thus been to efficiently estimate the amount of information that these dynamics convey from experimental data. Here we develop and evaluate decoding-based estimation methods to lower bound the mutual information about a finite set of inputs, encoded in single-cell high-dimensional time series data. For biological reaction networks governed by the chemical Master equation, we derive model-based information approximations and analytical upper bounds, against which we benchmark our proposed model-free decoding estimators. In contrast to the frequently-used k-nearest-neighbor estimator, decoding-based estimators robustly extract a large fraction of the available information from high-dimensional trajectories with a realistic number of data samples. We apply these estimators to previously published data on Erk and Ca2+ signaling in mammalian cells and to yeast stress-response, and find that substantial amount of information about environmental state can be encoded by non-trivial response statistics even in stationary signals. We argue that these single-cell, decoding-based information estimates, rather than the commonly-used tests for significant differences between selected population response statistics, provide a proper and unbiased measure for the performance of biological signaling networks.","lang":"eng"}],"file_date_updated":"2020-07-14T12:47:44Z","publication_status":"published","publication_identifier":{"eissn":["15537358"]},"scopus_import":"1","day":"03","author":[{"full_name":"Cepeda Humerez, Sarah A","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","last_name":"Cepeda Humerez","first_name":"Sarah A"},{"full_name":"Ruess, Jakob","last_name":"Ruess","orcid":"0000-0003-1615-3282","first_name":"Jakob"},{"first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","last_name":"Tkačik"}],"oa_version":"Published Version","title":"Estimating information in time-varying signals","volume":15,"date_created":"2019-09-22T22:00:37Z"},{"year":"2019","month":"12","arxiv":1,"external_id":{"arxiv":["1912.08579"]},"department":[{"_id":"GaTk"}],"oa":1,"publication":"arXiv:1912.08579","status":"public","language":[{"iso":"eng"}],"project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation"}],"citation":{"ieee":"W. Bialek, T. Gregor, and G. Tkačik, “Action at a distance in transcriptional regulation,” <i>arXiv:1912.08579</i>. ArXiv.","short":"W. Bialek, T. Gregor, G. Tkačik, ArXiv:1912.08579 (n.d.).","ama":"Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation. <i>arXiv:191208579</i>.","apa":"Bialek, W., Gregor, T., &#38; Tkačik, G. (n.d.). Action at a distance in transcriptional regulation. <i>arXiv:1912.08579</i>. ArXiv.","mla":"Bialek, William, et al. “Action at a Distance in Transcriptional Regulation.” <i>ArXiv:1912.08579</i>, ArXiv.","ista":"Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation. arXiv:1912.08579, .","chicago":"Bialek, William, Thomas Gregor, and Gašper Tkačik. “Action at a Distance in Transcriptional Regulation.” <i>ArXiv:1912.08579</i>. ArXiv, n.d."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2019-12-18T00:00:00Z","day":"18","article_processing_charge":"No","author":[{"full_name":"Bialek, William","last_name":"Bialek","first_name":"William"},{"full_name":"Gregor, Thomas","last_name":"Gregor","first_name":"Thomas"},{"last_name":"Tkačik","full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","orcid":"0000-0002-6699-1455"}],"title":"Action at a distance in transcriptional regulation","oa_version":"Preprint","publisher":"ArXiv","_id":"7552","date_updated":"2021-01-12T08:14:09Z","date_created":"2020-02-28T10:57:08Z","type":"preprint","page":"5","abstract":[{"text":"There is increasing evidence that protein binding to specific sites along DNA can activate the reading out of genetic information without coming into direct physical contact with the gene. There also is evidence that these distant but interacting sites are embedded in a liquid droplet of proteins which condenses out of the surrounding solution. We argue that droplet-mediated interactions can account for crucial features of gene regulation only if the droplet is poised at a non-generic point in its phase diagram. We explore a minimal model that embodies this idea, show that this model has a natural mechanism for self-tuning, and suggest direct experimental tests. ","lang":"eng"}],"main_file_link":[{"url":"https://arxiv.org/abs/1912.08579","open_access":"1"}],"publication_status":"submitted"},{"oa_version":"Published Version","title":"Optimal decoding of cellular identities in a genetic network","author":[{"first_name":"Mariela D.","full_name":"Petkova, Mariela D.","last_name":"Petkova"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","orcid":"0000-0002-6699-1455","first_name":"Gasper"},{"first_name":"William","last_name":"Bialek","full_name":"Bialek, William"},{"first_name":"Eric F.","last_name":"Wieschaus","full_name":"Wieschaus, Eric F."},{"first_name":"Thomas","full_name":"Gregor, Thomas","last_name":"Gregor"}],"scopus_import":"1","day":"07","article_type":"original","date_created":"2019-02-10T22:59:16Z","volume":176,"intvolume":"       176","abstract":[{"lang":"eng","text":"In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy."}],"publication_status":"published","month":"02","department":[{"_id":"GaTk"}],"language":[{"iso":"eng"}],"oa":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","issue":"4","citation":{"chicago":"Petkova, Mariela D., Gašper Tkačik, William Bialek, Eric F. Wieschaus, and Thomas Gregor. “Optimal Decoding of Cellular Identities in a Genetic Network.” <i>Cell</i>. Cell Press, 2019. <a href=\"https://doi.org/10.1016/j.cell.2019.01.007\">https://doi.org/10.1016/j.cell.2019.01.007</a>.","ista":"Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. 2019. Optimal decoding of cellular identities in a genetic network. Cell. 176(4), 844–855.e15.","mla":"Petkova, Mariela D., et al. “Optimal Decoding of Cellular Identities in a Genetic Network.” <i>Cell</i>, vol. 176, no. 4, Cell Press, 2019, p. 844–855.e15, doi:<a href=\"https://doi.org/10.1016/j.cell.2019.01.007\">10.1016/j.cell.2019.01.007</a>.","apa":"Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., &#38; Gregor, T. (2019). Optimal decoding of cellular identities in a genetic network. <i>Cell</i>. Cell Press. <a href=\"https://doi.org/10.1016/j.cell.2019.01.007\">https://doi.org/10.1016/j.cell.2019.01.007</a>","ama":"Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. Optimal decoding of cellular identities in a genetic network. <i>Cell</i>. 2019;176(4):844-855.e15. doi:<a href=\"https://doi.org/10.1016/j.cell.2019.01.007\">10.1016/j.cell.2019.01.007</a>","short":"M.D. Petkova, G. Tkačik, W. Bialek, E.F. Wieschaus, T. Gregor, Cell 176 (2019) 844–855.e15.","ieee":"M. D. Petkova, G. Tkačik, W. Bialek, E. F. Wieschaus, and T. Gregor, “Optimal decoding of cellular identities in a genetic network,” <i>Cell</i>, vol. 176, no. 4. Cell Press, p. 844–855.e15, 2019."},"publisher":"Cell Press","doi":"10.1016/j.cell.2019.01.007","article_processing_charge":"No","type":"journal_article","date_updated":"2023-08-24T14:42:47Z","_id":"5945","page":"844-855.e15","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.cell.2019.01.007"}],"external_id":{"isi":["000457969200015"],"pmid":["30712870"]},"related_material":{"link":[{"relation":"press_release","url":"https://ist.ac.at/en/news/cells-find-their-identity-using-a-mathematically-optimal-strategy/","description":"News on IST Homepage"}]},"isi":1,"year":"2019","project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"publication":"Cell","status":"public","date_published":"2019-02-07T00:00:00Z","pmid":1},{"type":"dissertation","date_updated":"2025-05-28T11:57:05Z","_id":"6071","publisher":"Institute of Science and Technology Austria","doi":"10.15479/at:ista:th6071","article_processing_charge":"No","alternative_title":["ISTA Thesis"],"ddc":["576"],"page":"189","related_material":{"record":[{"id":"1358","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","status":"public","id":"955"}]},"year":"2019","date_published":"2019-03-11T00:00:00Z","project":[{"call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"status":"public","degree_awarded":"PhD","date_created":"2019-03-06T16:16:10Z","oa_version":"Published Version","title":"Coevolution of transcription factors and their binding sites in sequence space","author":[{"last_name":"Prizak","id":"4456104E-F248-11E8-B48F-1D18A9856A87","full_name":"Prizak, Roshan","first_name":"Roshan"}],"day":"11","publication_identifier":{"issn":["2663-337X"]},"publication_status":"published","file_date_updated":"2020-07-14T12:47:18Z","abstract":[{"text":"Transcription factors, by binding to specific sequences on the DNA, control the precise spatio-temporal expression of genes inside a cell. However, this specificity is limited, leading to frequent incorrect binding of transcription factors that might have deleterious consequences on the cell. By constructing a biophysical model of TF-DNA binding in the context of gene regulation, I will first explore how regulatory constraints can strongly shape the distribution of a population in sequence space. Then, by directly linking this to a picture of multiple types of transcription factors performing their functions simultaneously inside the cell, I will explore the extent of regulatory crosstalk -- incorrect binding interactions between transcription factors and binding sites that lead to erroneous regulatory states -- and understand the constraints this places on the design of regulatory systems. I will then develop a generic theoretical framework to investigate the coevolution of multiple transcription factors and multiple binding sites, in the context of a gene regulatory network that performs a certain function. As a particular tractable version of this problem, I will consider the evolution of two transcription factors when they transmit upstream signals to downstream target genes. Specifically, I will describe the evolutionary steady states and the evolutionary pathways involved, along with their timescales, of a system that initially undergoes a transcription factor duplication event. To connect this important theoretical model to the prominent biological event of transcription factor duplication giving rise to paralogous families, I will then describe a bioinformatics analysis of C2H2 Zn-finger transcription factors, a major family in humans, and focus on the patterns of evolution that paralogs have undergone in their various protein domains in the recent past. ","lang":"eng"}],"has_accepted_license":"1","file":[{"checksum":"e60a72de35d270b31f1a23d50f224ec0","relation":"main_file","content_type":"application/pdf","access_level":"open_access","file_name":"Thesis_final_PDFA_RoshanPrizak.pdf","file_id":"6072","date_updated":"2020-07-14T12:47:18Z","creator":"rprizak","date_created":"2019-03-06T16:05:07Z","file_size":20995465},{"access_level":"closed","content_type":"application/zip","file_name":"thesis_v2_merge.zip","checksum":"67c2630333d05ebafef5f018863a8465","relation":"source_file","date_updated":"2020-07-14T12:47:18Z","creator":"rprizak","date_created":"2019-03-06T16:09:39Z","file_size":85705272,"file_id":"6073","title":"Latex files"}],"department":[{"_id":"GaTk"},{"_id":"NiBa"}],"month":"03","supervisor":[{"first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","last_name":"Tkačik"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"ista":"Prizak R. 2019. Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria.","chicago":"Prizak, Roshan. “Coevolution of Transcription Factors and Their Binding Sites in Sequence Space.” Institute of Science and Technology Austria, 2019. <a href=\"https://doi.org/10.15479/at:ista:th6071\">https://doi.org/10.15479/at:ista:th6071</a>.","apa":"Prizak, R. (2019). <i>Coevolution of transcription factors and their binding sites in sequence space</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:th6071\">https://doi.org/10.15479/at:ista:th6071</a>","mla":"Prizak, Roshan. <i>Coevolution of Transcription Factors and Their Binding Sites in Sequence Space</i>. Institute of Science and Technology Austria, 2019, doi:<a href=\"https://doi.org/10.15479/at:ista:th6071\">10.15479/at:ista:th6071</a>.","ama":"Prizak R. Coevolution of transcription factors and their binding sites in sequence space. 2019. doi:<a href=\"https://doi.org/10.15479/at:ista:th6071\">10.15479/at:ista:th6071</a>","ieee":"R. Prizak, “Coevolution of transcription factors and their binding sites in sequence space,” Institute of Science and Technology Austria, 2019.","short":"R. Prizak, Coevolution of Transcription Factors and Their Binding Sites in Sequence Space, Institute of Science and Technology Austria, 2019."},"language":[{"iso":"eng"}],"oa":1},{"page":"6088 - 6093","main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/content/early/2017/09/21/192039"}],"quality_controlled":"1","doi":"10.1073/pnas.1716659115","article_processing_charge":"No","publisher":"National Academy of Sciences","date_updated":"2023-09-11T12:58:24Z","_id":"281","type":"journal_article","project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"status":"public","publication":"PNAS","pmid":1,"date_published":"2018-06-05T00:00:00Z","acknowledgement":"This work was supported by the Biotechnology and Biological Sciences Research Council (J.M.J.P., I.F., and P.S.S.), the Engineering and Physical Sciences Research Council (EPSRC) (A.A.G.), and Austrian Science Fund Grant FWF P28844 (to G.T.).","isi":1,"year":"2018","external_id":{"isi":["000434114900071"],"pmid":["29784812"]},"related_material":{"record":[{"id":"6473","relation":"part_of_dissertation","status":"public"}]},"publist_id":"7618","abstract":[{"lang":"eng","text":"Although cells respond specifically to environments, how environmental identity is encoded intracellularly is not understood. Here, we study this organization of information in budding yeast by estimating the mutual information between environmental transitions and the dynamics of nuclear translocation for 10 transcription factors. Our method of estimation is general, scalable, and based on decoding from single cells. The dynamics of the transcription factors are necessary to encode the highest amounts of extracellular information, and we show that information is transduced through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can encode the nature of multiple stresses, but only if stress is high; specialists (Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly and for a wider range of magnitudes. In particular, Dot6 encodes almost as much information as Msn2, the master regulator of the environmental stress response. Each transcription factor reports differently, and it is only their collective behavior that distinguishes between multiple environmental states. Changes in the dynamics of the localization of transcription factors thus constitute a precise, distributed internal representation of extracellular change. We predict that such multidimensional representations are common in cellular decision-making."}],"intvolume":"       115","publication_status":"published","author":[{"first_name":"Alejandro","full_name":"Granados, Alejandro","last_name":"Granados"},{"last_name":"Pietsch","full_name":"Pietsch, Julian","first_name":"Julian"},{"last_name":"Cepeda Humerez","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","full_name":"Cepeda Humerez, Sarah A","first_name":"Sarah A"},{"first_name":"Isebail","last_name":"Farquhar","full_name":"Farquhar, Isebail"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455"},{"last_name":"Swain","full_name":"Swain, Peter","first_name":"Peter"}],"scopus_import":"1","day":"05","title":"Distributed and dynamic intracellular organization of extracellular information","oa_version":"Preprint","volume":115,"article_type":"original","date_created":"2018-12-11T11:45:35Z","oa":1,"language":[{"iso":"eng"}],"issue":"23","citation":{"ista":"Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. 2018. Distributed and dynamic intracellular organization of extracellular information. PNAS. 115(23), 6088–6093.","chicago":"Granados, Alejandro, Julian Pietsch, Sarah A Cepeda Humerez, Isebail Farquhar, Gašper Tkačik, and Peter Swain. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” <i>PNAS</i>. National Academy of Sciences, 2018. <a href=\"https://doi.org/10.1073/pnas.1716659115\">https://doi.org/10.1073/pnas.1716659115</a>.","apa":"Granados, A., Pietsch, J., Cepeda Humerez, S. A., Farquhar, I., Tkačik, G., &#38; Swain, P. (2018). Distributed and dynamic intracellular organization of extracellular information. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1716659115\">https://doi.org/10.1073/pnas.1716659115</a>","mla":"Granados, Alejandro, et al. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” <i>PNAS</i>, vol. 115, no. 23, National Academy of Sciences, 2018, pp. 6088–93, doi:<a href=\"https://doi.org/10.1073/pnas.1716659115\">10.1073/pnas.1716659115</a>.","ama":"Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. Distributed and dynamic intracellular organization of extracellular information. <i>PNAS</i>. 2018;115(23):6088-6093. doi:<a href=\"https://doi.org/10.1073/pnas.1716659115\">10.1073/pnas.1716659115</a>","ieee":"A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkačik, and P. Swain, “Distributed and dynamic intracellular organization of extracellular information,” <i>PNAS</i>, vol. 115, no. 23. National Academy of Sciences, pp. 6088–6093, 2018.","short":"A. Granados, J. Pietsch, S.A. Cepeda Humerez, I. Farquhar, G. Tkačik, P. Swain, PNAS 115 (2018) 6088–6093."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","month":"06","department":[{"_id":"GaTk"}]},{"status":"public","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"},{"grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"ec_funded":1,"date_published":"2018-09-21T00:00:00Z","year":"2018","related_material":{"record":[{"id":"161","status":"public","relation":"research_paper"}]},"keyword":["metabolic networks","e.coli core","maximum entropy","monte carlo markov chain sampling","ellipsoidal rounding"],"ddc":["530"],"article_processing_charge":"No","doi":"10.15479/AT:ISTA:62","publisher":"Institute of Science and Technology Austria","_id":"5587","date_updated":"2024-02-21T13:45:39Z","type":"research_data","oa":1,"citation":{"mla":"De Martino, Daniele, and Gašper Tkačik. <i>Supporting Materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.”</i> Institute of Science and Technology Austria, 2018, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:62\">10.15479/AT:ISTA:62</a>.","apa":"De Martino, D., &#38; Tkačik, G. (2018). Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:62\">https://doi.org/10.15479/AT:ISTA:62</a>","chicago":"De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018. <a href=\"https://doi.org/10.15479/AT:ISTA:62\">https://doi.org/10.15479/AT:ISTA:62</a>.","ista":"De Martino D, Tkačik G. 2018. Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:62\">10.15479/AT:ISTA:62</a>.","short":"D. De Martino, G. Tkačik, (2018).","ieee":"D. De Martino and G. Tkačik, “Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018.","ama":"De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:62\">10.15479/AT:ISTA:62</a>"},"datarep_id":"111","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"09","department":[{"_id":"GaTk"}],"file":[{"file_name":"IST-2018-111-v1+1_CODES.zip","access_level":"open_access","content_type":"application/zip","relation":"main_file","checksum":"97992e3e8cf8544ec985a48971708726","date_created":"2018-12-12T13:05:13Z","file_size":14376,"creator":"system","date_updated":"2020-07-14T12:47:08Z","file_id":"5641"}],"has_accepted_license":"1","abstract":[{"text":"Supporting material to the article \r\nSTATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH\r\n\r\nboundscoli.dat\r\nFlux Bounds of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium. \r\n\r\npolcoli.dat\r\nMatrix enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium, \r\nobtained from the soichiometric matrix by standard linear algebra  (reduced row echelon form).\r\n\r\nellis.dat\r\nApproximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\npoint0.dat\r\nCenter of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\nlovasz.cpp  \r\nThis c++ code file receives in input the polytope of the feasible steady states of a metabolic network, \r\n(matrix and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding the polytope\r\nwith the Lovasz method \r\nNB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we refer to  PLoS ONE 10.4 e0122670 (2015).\r\n\r\nsampleHRnew.cpp  \r\nThis c++ code file receives in input the polytope of the feasible steady states of a metabolic network, \r\n(matrix and bounds), the ellipsoid rounding the polytope, a point inside and  \r\nit gives in output a max entropy sampling at fixed average growth rate \r\nof the steady states by performing an Hit-and-Run Monte Carlo Markov chain.\r\nNB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we refer to  PLoS ONE 10.4 e0122670 (2015).","lang":"eng"}],"tmp":{"name":"Creative Commons Public Domain Dedication (CC0 1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","image":"/images/cc_0.png","short":"CC0 (1.0)"},"license":"https://creativecommons.org/publicdomain/zero/1.0/","file_date_updated":"2020-07-14T12:47:08Z","day":"21","author":[{"last_name":"De Martino","full_name":"De Martino, Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","first_name":"Daniele"},{"last_name":"Tkacik","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper","orcid":"0000-0002-6699-1455"}],"title":"Supporting materials \"STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH\"","oa_version":"Published Version","date_created":"2018-12-12T12:31:41Z"},{"ec_funded":1,"date_published":"2018-07-30T00:00:00Z","status":"public","publication":"Nature Communications","project":[{"call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"},{"_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734"}],"publist_id":"7760","year":"2018","isi":1,"related_material":{"record":[{"id":"5587","status":"public","relation":"popular_science"}]},"external_id":{"isi":["000440149300021"]},"quality_controlled":"1","ddc":["570"],"_id":"161","date_updated":"2024-02-21T13:45:39Z","type":"journal_article","article_processing_charge":"No","doi":"10.1038/s41467-018-05417-9","publisher":"Springer Nature","citation":{"short":"D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications 9 (2018).","ieee":"D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical mechanics for metabolic networks during steady state growth,” <i>Nature Communications</i>, vol. 9, no. 1. Springer Nature, 2018.","ama":"De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics for metabolic networks during steady state growth. <i>Nature Communications</i>. 2018;9(1). doi:<a href=\"https://doi.org/10.1038/s41467-018-05417-9\">10.1038/s41467-018-05417-9</a>","mla":"De Martino, Daniele, et al. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” <i>Nature Communications</i>, vol. 9, no. 1, 2988, Springer Nature, 2018, doi:<a href=\"https://doi.org/10.1038/s41467-018-05417-9\">10.1038/s41467-018-05417-9</a>.","apa":"De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., &#38; Tkačik, G. (2018). Statistical mechanics for metabolic networks during steady state growth. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-018-05417-9\">https://doi.org/10.1038/s41467-018-05417-9</a>","chicago":"De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet, and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” <i>Nature Communications</i>. Springer Nature, 2018. <a href=\"https://doi.org/10.1038/s41467-018-05417-9\">https://doi.org/10.1038/s41467-018-05417-9</a>.","ista":"De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 9(1), 2988."},"issue":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa":1,"language":[{"iso":"eng"}],"department":[{"_id":"GaTk"},{"_id":"CaGu"}],"file":[{"checksum":"3ba7ab27b27723c7dcf633e8fc1f8f18","relation":"main_file","content_type":"application/pdf","access_level":"open_access","file_name":"2018_NatureComm_DeMartino.pdf","file_id":"5728","creator":"dernst","date_updated":"2020-07-14T12:45:06Z","date_created":"2018-12-17T16:44:28Z","file_size":1043205}],"article_number":"2988","month":"07","file_date_updated":"2020-07-14T12:45:06Z","publication_status":"published","has_accepted_license":"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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"intvolume":"         9","abstract":[{"lang":"eng","text":"Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells."}],"volume":9,"date_created":"2018-12-11T11:44:57Z","day":"30","scopus_import":"1","author":[{"first_name":"Daniele","orcid":"0000-0002-5214-4706","last_name":"De Martino","full_name":"De Martino, Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Mc","full_name":"Mc, Andersson Anna","first_name":"Andersson Anna"},{"last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","full_name":"Bergmiller, Tobias","orcid":"0000-0001-5396-4346","first_name":"Tobias"},{"first_name":"Calin C","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet"},{"orcid":"0000-0002-6699-1455","first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper"}],"title":"Statistical mechanics for metabolic networks during steady state growth","oa_version":"Published Version"},{"department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"Bio"}],"month":"04","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Bergmiller, Tobias, et al. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” <i>Science</i>, vol. 356, no. 6335, American Association for the Advancement of Science, 2017, pp. 311–15, doi:<a href=\"https://doi.org/10.1126/science.aaf4762\">10.1126/science.aaf4762</a>.","apa":"Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. <i>Science</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/science.aaf4762\">https://doi.org/10.1126/science.aaf4762</a>","chicago":"Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” <i>Science</i>. American Association for the Advancement of Science, 2017. <a href=\"https://doi.org/10.1126/science.aaf4762\">https://doi.org/10.1126/science.aaf4762</a>.","ista":"Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik G, Guet CC. 2017. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. 356(6335), 311–315.","short":"T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, Science 356 (2017) 311–315.","ieee":"T. Bergmiller <i>et al.</i>, “Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity,” <i>Science</i>, vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315, 2017.","ama":"Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. <i>Science</i>. 2017;356(6335):311-315. doi:<a href=\"https://doi.org/10.1126/science.aaf4762\">10.1126/science.aaf4762</a>"},"issue":"6335","language":[{"iso":"eng"}],"date_created":"2018-12-11T11:47:48Z","article_type":"original","volume":356,"oa_version":"None","title":"Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity","day":"21","scopus_import":1,"author":[{"first_name":"Tobias","orcid":"0000-0001-5396-4346","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","full_name":"Bergmiller, Tobias","last_name":"Bergmiller"},{"orcid":"0000-0003-2912-6769","first_name":"Anna M","id":"2B8A40DA-F248-11E8-B48F-1D18A9856A87","full_name":"Andersson, Anna M","last_name":"Andersson"},{"full_name":"Tomasek, Kathrin","id":"3AEC8556-F248-11E8-B48F-1D18A9856A87","last_name":"Tomasek","orcid":"0000-0003-3768-877X","first_name":"Kathrin"},{"first_name":"Enrique","full_name":"Balleza, Enrique","last_name":"Balleza"},{"full_name":"Kiviet, Daniel","last_name":"Kiviet","first_name":"Daniel"},{"last_name":"Hauschild","full_name":"Hauschild, Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","first_name":"Robert","orcid":"0000-0001-9843-3522"},{"last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","first_name":"Gasper","orcid":"0000-0002-6699-1455"},{"first_name":"Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C"}],"publication_identifier":{"issn":["00368075"]},"publication_status":"published","intvolume":"       356","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."}],"publist_id":"7064","related_material":{"record":[{"id":"5560","relation":"popular_science","status":"public"}]},"year":"2017","date_published":"2017-04-21T00:00:00Z","status":"public","publication":"Science","project":[{"call_identifier":"FWF","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"type":"journal_article","_id":"665","date_updated":"2024-02-21T13:49:00Z","publisher":"American Association for the Advancement of Science","article_processing_charge":"No","doi":"10.1126/science.aaf4762","quality_controlled":"1","page":"311 - 315"},{"quality_controlled":"1","ddc":["576","579"],"_id":"613","date_updated":"2021-01-12T08:06:15Z","type":"journal_article","article_processing_charge":"Yes (in subscription journal)","doi":"10.1038/s41467-017-01683-1","publisher":"Nature Publishing Group","ec_funded":1,"date_published":"2017-12-01T00:00:00Z","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).","status":"public","publication":"Nature Communications","project":[{"name":"International IST Postdoc Fellowship Programme","grant_number":"291734","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425"},{"name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"publist_id":"7191","year":"2017","file_date_updated":"2020-07-14T12:47:20Z","publication_identifier":{"issn":["20411723"]},"publication_status":"published","has_accepted_license":"1","intvolume":"         8","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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"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."}],"volume":8,"date_created":"2018-12-11T11:47:30Z","day":"01","scopus_import":1,"author":[{"orcid":"0000-0003-0876-3187","first_name":"Remy P","full_name":"Chait, Remy P","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","last_name":"Chait"},{"last_name":"Ruess","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","full_name":"Ruess, Jakob","first_name":"Jakob","orcid":"0000-0003-1615-3282"},{"orcid":"0000-0001-5396-4346","first_name":"Tobias","full_name":"Bergmiller, Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","last_name":"Bergmiller"},{"orcid":"0000-0002-6699-1455","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik"},{"full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","orcid":"0000-0001-6220-2052","first_name":"Calin C"}],"title":"Shaping bacterial population behavior through computer interfaced control of individual cells","oa_version":"Published Version","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,” <i>Nature Communications</i>, vol. 8, no. 1. Nature Publishing Group, 2017.","short":"R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications 8 (2017).","ama":"Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population behavior through computer interfaced control of individual cells. <i>Nature Communications</i>. 2017;8(1). doi:<a href=\"https://doi.org/10.1038/s41467-017-01683-1\">10.1038/s41467-017-01683-1</a>","apa":"Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., &#38; Guet, C. C. (2017). Shaping bacterial population behavior through computer interfaced control of individual cells. <i>Nature Communications</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/s41467-017-01683-1\">https://doi.org/10.1038/s41467-017-01683-1</a>","mla":"Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” <i>Nature Communications</i>, vol. 8, no. 1, 1535, Nature Publishing Group, 2017, doi:<a href=\"https://doi.org/10.1038/s41467-017-01683-1\">10.1038/s41467-017-01683-1</a>.","chicago":"Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” <i>Nature Communications</i>. Nature Publishing Group, 2017. <a href=\"https://doi.org/10.1038/s41467-017-01683-1\">https://doi.org/10.1038/s41467-017-01683-1</a>.","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."},"issue":"1","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa":1,"language":[{"iso":"eng"}],"pubrep_id":"911","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"file":[{"date_created":"2018-12-12T10:16:05Z","file_size":1951699,"creator":"system","date_updated":"2020-07-14T12:47:20Z","file_id":"5190","file_name":"IST-2017-911-v1+1_s41467-017-01683-1.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"44bb5d0229926c23a9955d9fe0f9723f"}],"article_number":"1535","month":"12"},{"page":"1379 - 1383","quality_controlled":"1","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/","open_access":"1"}],"publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aam5887","article_processing_charge":"No","type":"journal_article","date_updated":"2023-09-26T15:38:05Z","_id":"943","project":[{"call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"},{"call_identifier":"H2020","grant_number":"680037","name":"Coordination of Patterning And Growth In the Spinal Cord","_id":"B6FC0238-B512-11E9-945C-1524E6697425"},{"_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","call_identifier":"FP7"},{"call_identifier":"FP7","name":"Developing High-Throughput Bioassays for Human Cancers in Zebrafish","grant_number":"201439","_id":"2524F500-B435-11E9-9278-68D0E5697425"}],"publication":"Science","status":"public","date_published":"2017-06-30T00:00:00Z","pmid":1,"ec_funded":1,"external_id":{"isi":["000404351500036"],"pmid":["28663499"]},"isi":1,"year":"2017","publist_id":"6474","abstract":[{"lang":"eng","text":"Like many developing tissues, the vertebrate neural tube is patterned by antiparallel morphogen gradients. To understand how these inputs are interpreted, we measured morphogen signaling and target gene expression in mouse embryos and chick ex vivo assays. From these data, we derived and validated a characteristic decoding map that relates morphogen input to the positional identity of neural progenitors. Analysis of the observed responses indicates that the underlying interpretation strategy minimizes patterning errors in response to the joint input of noisy opposing gradients. We reverse-engineered a transcriptional network that provides a mechanistic basis for the observed cell fate decisions and accounts for the precision and dynamics of pattern formation. Together, our data link opposing gradient dynamics in a growing tissue to precise pattern formation."}],"intvolume":"       356","publication_identifier":{"issn":["00368075"]},"publication_status":"published","oa_version":"Submitted Version","title":"Decoding of position in the developing neural tube from antiparallel morphogen gradients","author":[{"orcid":"0000-0001-7896-7762","first_name":"Marcin P","last_name":"Zagórski","full_name":"Zagórski, Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Tabata","full_name":"Tabata, Yoji","first_name":"Yoji"},{"first_name":"Nathalie","full_name":"Brandenberg, Nathalie","last_name":"Brandenberg"},{"first_name":"Matthias","last_name":"Lutolf","full_name":"Lutolf, Matthias"},{"last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","orcid":"0000-0002-6699-1455","first_name":"Gasper"},{"first_name":"Tobias","full_name":"Bollenbach, Tobias","last_name":"Bollenbach"},{"first_name":"James","last_name":"Briscoe","full_name":"Briscoe, James"},{"id":"3959A2A0-F248-11E8-B48F-1D18A9856A87","full_name":"Kicheva, Anna","last_name":"Kicheva","first_name":"Anna","orcid":"0000-0003-4509-4998"}],"day":"30","scopus_import":"1","date_created":"2018-12-11T11:49:20Z","volume":356,"language":[{"iso":"eng"}],"oa":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","issue":"6345","citation":{"ama":"Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing neural tube from antiparallel morphogen gradients. <i>Science</i>. 2017;356(6345):1379-1383. doi:<a href=\"https://doi.org/10.1126/science.aam5887\">10.1126/science.aam5887</a>","short":"M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach, J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.","ieee":"M. P. Zagórski <i>et al.</i>, “Decoding of position in the developing neural tube from antiparallel morphogen gradients,” <i>Science</i>, vol. 356, no. 6345. American Association for the Advancement of Science, pp. 1379–1383, 2017.","ista":"Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 356(6345), 1379–1383.","chicago":"Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf, Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” <i>Science</i>. American Association for the Advancement of Science, 2017. <a href=\"https://doi.org/10.1126/science.aam5887\">https://doi.org/10.1126/science.aam5887</a>.","mla":"Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” <i>Science</i>, vol. 356, no. 6345, American Association for the Advancement of Science, 2017, pp. 1379–83, doi:<a href=\"https://doi.org/10.1126/science.aam5887\">10.1126/science.aam5887</a>.","apa":"Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach, T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from antiparallel morphogen gradients. <i>Science</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/science.aam5887\">https://doi.org/10.1126/science.aam5887</a>"},"month":"06","department":[{"_id":"AnKi"},{"_id":"GaTk"}]},{"language":[{"iso":"eng"}],"pubrep_id":"864","oa":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"ama":"Friedlander T, Prizak R, Barton NH, Tkačik G. Evolution of new regulatory functions on biophysically realistic fitness landscapes. <i>Nature Communications</i>. 2017;8(1). doi:<a href=\"https://doi.org/10.1038/s41467-017-00238-8\">10.1038/s41467-017-00238-8</a>","short":"T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications 8 (2017).","ieee":"T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new regulatory functions on biophysically realistic fitness landscapes,” <i>Nature Communications</i>, vol. 8, no. 1. Nature Publishing Group, 2017.","chicago":"Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” <i>Nature Communications</i>. Nature Publishing Group, 2017. <a href=\"https://doi.org/10.1038/s41467-017-00238-8\">https://doi.org/10.1038/s41467-017-00238-8</a>.","ista":"Friedlander T, Prizak R, Barton NH, Tkačik G. 2017. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 8(1), 216.","mla":"Friedlander, Tamar, et al. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” <i>Nature Communications</i>, vol. 8, no. 1, 216, Nature Publishing Group, 2017, doi:<a href=\"https://doi.org/10.1038/s41467-017-00238-8\">10.1038/s41467-017-00238-8</a>.","apa":"Friedlander, T., Prizak, R., Barton, N. H., &#38; Tkačik, G. (2017). Evolution of new regulatory functions on biophysically realistic fitness landscapes. <i>Nature Communications</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/s41467-017-00238-8\">https://doi.org/10.1038/s41467-017-00238-8</a>"},"issue":"1","month":"08","article_number":"216","file":[{"file_name":"IST-2017-864-v1+1_s41467-017-00238-8.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"29a1b5db458048d3bd5c67e0e2a56818","file_size":998157,"date_created":"2018-12-12T10:14:14Z","creator":"system","date_updated":"2020-07-14T12:48:16Z","file_id":"5064"},{"relation":"main_file","checksum":"7b78401e52a576cf3e6bbf8d0abadc17","file_name":"IST-2017-864-v1+2_41467_2017_238_MOESM1_ESM.pdf","access_level":"open_access","content_type":"application/pdf","file_id":"5065","file_size":9715993,"date_created":"2018-12-12T10:14:15Z","date_updated":"2020-07-14T12:48:16Z","creator":"system"}],"department":[{"_id":"GaTk"},{"_id":"NiBa"}],"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."}],"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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"intvolume":"         8","has_accepted_license":"1","file_date_updated":"2020-07-14T12:48:16Z","publication_identifier":{"issn":["20411723"]},"publication_status":"published","oa_version":"Published Version","title":"Evolution of new regulatory functions on biophysically realistic fitness landscapes","day":"09","scopus_import":"1","author":[{"first_name":"Tamar","last_name":"Friedlander","full_name":"Friedlander, Tamar","id":"36A5845C-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Roshan","id":"4456104E-F248-11E8-B48F-1D18A9856A87","full_name":"Prizak, Roshan","last_name":"Prizak"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","first_name":"Nicholas H","orcid":"0000-0002-8548-5240"},{"first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik"}],"date_created":"2018-12-11T11:49:23Z","volume":8,"publication":"Nature Communications","status":"public","project":[{"grant_number":"291734","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"date_published":"2017-08-09T00:00:00Z","ec_funded":1,"related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"6071"}]},"external_id":{"isi":["000407198800005"]},"isi":1,"year":"2017","publist_id":"6459","ddc":["539","576"],"quality_controlled":"1","publisher":"Nature Publishing Group","article_processing_charge":"Yes (in subscription journal)","doi":"10.1038/s41467-017-00238-8","type":"journal_article","_id":"955","date_updated":"2025-05-28T11:42:50Z"},{"citation":{"ama":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to gene regulation by global crosstalk. <i>Nature Communications</i>. 2016;7. doi:<a href=\"https://doi.org/10.1038/ncomms12307\">10.1038/ncomms12307</a>","ieee":"T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic limits to gene regulation by global crosstalk,” <i>Nature Communications</i>, vol. 7. Nature Publishing Group, 2016.","short":"T. Friedlander, R. Prizak, C.C. Guet, N.H. Barton, G. Tkačik, Nature Communications 7 (2016).","chicago":"Friedlander, Tamar, Roshan Prizak, Calin C Guet, Nicholas H Barton, and Gašper Tkačik. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” <i>Nature Communications</i>. Nature Publishing Group, 2016. <a href=\"https://doi.org/10.1038/ncomms12307\">https://doi.org/10.1038/ncomms12307</a>.","ista":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 7, 12307.","apa":"Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., &#38; Tkačik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. <i>Nature Communications</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/ncomms12307\">https://doi.org/10.1038/ncomms12307</a>","mla":"Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” <i>Nature Communications</i>, vol. 7, 12307, Nature Publishing Group, 2016, doi:<a href=\"https://doi.org/10.1038/ncomms12307\">10.1038/ncomms12307</a>."},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa":1,"language":[{"iso":"eng"}],"pubrep_id":"627","department":[{"_id":"GaTk"},{"_id":"NiBa"},{"_id":"CaGu"}],"file":[{"file_id":"4919","date_updated":"2020-07-14T12:44:46Z","creator":"system","file_size":861805,"date_created":"2018-12-12T10:12:01Z","checksum":"fe3f3a1526d180b29fe691ab11435b78","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_name":"IST-2016-627-v1+1_ncomms12307.pdf"},{"access_level":"open_access","content_type":"application/pdf","file_name":"IST-2016-627-v1+2_ncomms12307-s1.pdf","checksum":"164864a1a675f3ad80e9917c27aba07f","relation":"main_file","creator":"system","date_updated":"2020-07-14T12:44:46Z","date_created":"2018-12-12T10:12:02Z","file_size":1084703,"file_id":"4920"}],"article_number":"12307","month":"08","publication_status":"published","file_date_updated":"2020-07-14T12:44:46Z","has_accepted_license":"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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"abstract":[{"lang":"eng","text":"Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements."}],"intvolume":"         7","volume":7,"date_created":"2018-12-11T11:51:34Z","author":[{"first_name":"Tamar","full_name":"Friedlander, Tamar","id":"36A5845C-F248-11E8-B48F-1D18A9856A87","last_name":"Friedlander"},{"last_name":"Prizak","full_name":"Prizak, Roshan","id":"4456104E-F248-11E8-B48F-1D18A9856A87","first_name":"Roshan"},{"full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","orcid":"0000-0001-6220-2052","first_name":"Calin C"},{"first_name":"Nicholas H","orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H","last_name":"Barton"},{"last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","first_name":"Gasper","orcid":"0000-0002-6699-1455"}],"day":"04","scopus_import":1,"title":"Intrinsic limits to gene regulation by global crosstalk","oa_version":"Published Version","ec_funded":1,"date_published":"2016-08-04T00:00:00Z","project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"291734","name":"International IST Postdoc Fellowship Programme"},{"name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425"},{"_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation"}],"status":"public","publication":"Nature Communications","publist_id":"5887","year":"2016","related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"6071"}]},"quality_controlled":"1","ddc":["576"],"date_updated":"2023-09-07T12:53:49Z","_id":"1358","type":"journal_article","doi":"10.1038/ncomms12307","publisher":"Nature Publishing Group"},{"date_updated":"2021-01-12T06:49:20Z","_id":"1242","type":"journal_article","doi":"10.1103/PhysRevE.93.022404","publisher":"American Institute of Physics","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1507.02562"}],"quality_controlled":"1","publist_id":"6088","year":"2016","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.","date_published":"2016-02-04T00:00:00Z","project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","call_identifier":"FWF"}],"status":"public","publication":"Physical Review E Statistical Nonlinear and Soft Matter Physics","volume":93,"date_created":"2018-12-11T11:50:54Z","author":[{"orcid":"0000-0002-1287-3779","first_name":"Thomas R","full_name":"Sokolowski, Thomas R","id":"3E999752-F248-11E8-B48F-1D18A9856A87","last_name":"Sokolowski"},{"first_name":"Aleksandra","full_name":"Walczak, Aleksandra","last_name":"Walczak"},{"last_name":"Bialek","full_name":"Bialek, William","first_name":"William"},{"orcid":"0000-0002-6699-1455","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik"}],"day":"04","scopus_import":1,"title":"Extending the dynamic range of transcription factor action by translational regulation","oa_version":"Preprint","publication_status":"published","intvolume":"        93","abstract":[{"lang":"eng","text":"A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression."}],"department":[{"_id":"GaTk"}],"article_number":"022404","month":"02","issue":"2","citation":{"ama":"Sokolowski TR, Walczak A, Bialek W, Tkačik G. Extending the dynamic range of transcription factor action by translational regulation. <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. 2016;93(2). doi:<a href=\"https://doi.org/10.1103/PhysRevE.93.022404\">10.1103/PhysRevE.93.022404</a>","short":"T.R. Sokolowski, A. Walczak, W. Bialek, G. Tkačik, Physical Review E Statistical Nonlinear and Soft Matter Physics 93 (2016).","ieee":"T. R. Sokolowski, A. Walczak, W. Bialek, and G. Tkačik, “Extending the dynamic range of transcription factor action by translational regulation,” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>, vol. 93, no. 2. American Institute of Physics, 2016.","chicago":"Sokolowski, Thomas R, Aleksandra Walczak, William Bialek, and Gašper Tkačik. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. American Institute of Physics, 2016. <a href=\"https://doi.org/10.1103/PhysRevE.93.022404\">https://doi.org/10.1103/PhysRevE.93.022404</a>.","ista":"Sokolowski TR, Walczak A, Bialek W, Tkačik G. 2016. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. 93(2), 022404.","mla":"Sokolowski, Thomas R., et al. “Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>, vol. 93, no. 2, 022404, American Institute of Physics, 2016, doi:<a href=\"https://doi.org/10.1103/PhysRevE.93.022404\">10.1103/PhysRevE.93.022404</a>.","apa":"Sokolowski, T. R., Walczak, A., Bialek, W., &#38; Tkačik, G. (2016). Extending the dynamic range of transcription factor action by translational regulation. <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. American Institute of Physics. <a href=\"https://doi.org/10.1103/PhysRevE.93.022404\">https://doi.org/10.1103/PhysRevE.93.022404</a>"},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa":1,"language":[{"iso":"eng"}]},{"related_material":{"record":[{"id":"9869","relation":"research_data","status":"public"},{"relation":"research_data","status":"public","id":"9870"},{"id":"9871","relation":"research_data","status":"public"}]},"year":"2016","publist_id":"6050","project":[{"name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"status":"public","publication":"PLoS One","date_published":"2016-09-27T00:00:00Z","acknowledgement":"The authors would like to thank Thomas Sokolowski and Filipe Tostevin for helpful discussions. PH and UG were funded by the German Excellence Initiative via the program \"Nanosystems Initiative Munich\" (https://www.nano-initiative-munich.de) and the German Research Foundation via the SFB 1032 \"Nanoagents for Spatiotemporal Control of Molecular and Cellular Reactions\" (http://www.sfb1032.physik.uni-muenchen.de). GT was funded by the Austrian Science Fund (FWF P 28844) (http://www.fwf.ac.at).","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0163628","type":"journal_article","date_updated":"2023-02-23T14:11:37Z","_id":"1270","ddc":["571"],"quality_controlled":"1","month":"09","article_number":"e0163628","file":[{"date_updated":"2020-07-14T12:44:42Z","creator":"system","file_size":4950415,"date_created":"2018-12-12T10:10:47Z","file_id":"4837","content_type":"application/pdf","access_level":"open_access","file_name":"IST-2016-696-v1+1_journal.pone.0163628.PDF","checksum":"3d0d55d373096a033bd9cf79288c8586","relation":"main_file"}],"department":[{"_id":"GaTk"}],"pubrep_id":"696","language":[{"iso":"eng"}],"oa":1,"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","issue":"9","citation":{"chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Beyond the French Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional Information.” <i>PLoS One</i>. Public Library of Science, 2016. <a href=\"https://doi.org/10.1371/journal.pone.0163628\">https://doi.org/10.1371/journal.pone.0163628</a>.","ista":"Hillenbrand P, Gerland U, Tkačik G. 2016. Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. 11(9), e0163628.","apa":"Hillenbrand, P., Gerland, U., &#38; Tkačik, G. (2016). Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. <i>PLoS One</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pone.0163628\">https://doi.org/10.1371/journal.pone.0163628</a>","mla":"Hillenbrand, Patrick, et al. “Beyond the French Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional Information.” <i>PLoS One</i>, vol. 11, no. 9, e0163628, Public Library of Science, 2016, doi:<a href=\"https://doi.org/10.1371/journal.pone.0163628\">10.1371/journal.pone.0163628</a>.","ama":"Hillenbrand P, Gerland U, Tkačik G. Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. <i>PLoS One</i>. 2016;11(9). doi:<a href=\"https://doi.org/10.1371/journal.pone.0163628\">10.1371/journal.pone.0163628</a>","ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information,” <i>PLoS One</i>, vol. 11, no. 9. Public Library of Science, 2016.","short":"P. Hillenbrand, U. Gerland, G. Tkačik, PLoS One 11 (2016)."},"oa_version":"Published Version","title":"Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information","author":[{"first_name":"Patrick","full_name":"Hillenbrand, Patrick","last_name":"Hillenbrand"},{"last_name":"Gerland","full_name":"Gerland, Ulrich","first_name":"Ulrich"},{"orcid":"0000-0002-6699-1455","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper","last_name":"Tkacik"}],"day":"27","scopus_import":1,"date_created":"2018-12-11T11:51:03Z","volume":11,"intvolume":"        11","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","image":"/images/cc_by.png","short":"CC BY (4.0)"},"abstract":[{"lang":"eng","text":"A crucial step in the early development of multicellular organisms involves the establishment of spatial patterns of gene expression which later direct proliferating cells to take on different cell fates. These patterns enable the cells to infer their global position within a tissue or an organism by reading out local gene expression levels. The patterning system is thus said to encode positional information, a concept that was formalized recently in the framework of information theory. Here we introduce a toy model of patterning in one spatial dimension, which can be seen as an extension of Wolpert's paradigmatic &quot;French Flag&quot; model, to patterning by several interacting, spatially coupled genes subject to intrinsic and extrinsic noise. Our model, a variant of an Ising spin system, allows us to systematically explore expression patterns that optimally encode positional information. We find that optimal patterning systems use positional cues, as in the French Flag model, together with gene-gene interactions to generate combinatorial codes for position which we call &quot;Counter&quot; patterns. Counter patterns can also be stabilized against noise and variations in system size or morphogen dosage by longer-range spatial interactions of the type invoked in the Turing model. The simple setup proposed here qualitatively captures many of the experimentally observed properties of biological patterning systems and allows them to be studied in a single, theoretically consistent framework."}],"has_accepted_license":"1","publication_status":"published","file_date_updated":"2020-07-14T12:44:42Z"}]