[{"oa_version":"Published Version","file":[{"checksum":"3d0d55d373096a033bd9cf79288c8586","date_created":"2018-12-12T10:10:47Z","date_updated":"2020-07-14T12:44:42Z","file_id":"4837","relation":"main_file","creator":"system","content_type":"application/pdf","file_size":4950415,"access_level":"open_access","file_name":"IST-2016-696-v1+1_journal.pone.0163628.PDF"}],"pubrep_id":"696","title":"Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information","ddc":["571"],"status":"public","intvolume":" 11","_id":"1270","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","abstract":[{"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 "French Flag" 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 "Counter" 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.","lang":"eng"}],"issue":"9","type":"journal_article","date_published":"2016-09-27T00:00:00Z","publication":"PLoS One","citation":{"chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Beyond the French Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional Information.” PLoS One. Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.","short":"P. Hillenbrand, U. Gerland, G. Tkačik, PLoS One 11 (2016).","mla":"Hillenbrand, Patrick, et al. “Beyond the French Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional Information.” PLoS One, vol. 11, no. 9, e0163628, Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.","apa":"Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628","ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information,” PLoS One, vol. 11, no. 9. Public Library of Science, 2016.","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.","ama":"Hillenbrand P, Gerland U, Tkačik G. Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. 2016;11(9). doi:10.1371/journal.pone.0163628"},"day":"27","has_accepted_license":"1","scopus_import":1,"date_created":"2018-12-11T11:51:03Z","date_updated":"2023-02-23T14:11:37Z","volume":11,"author":[{"full_name":"Hillenbrand, Patrick","last_name":"Hillenbrand","first_name":"Patrick"},{"last_name":"Gerland","first_name":"Ulrich","full_name":"Gerland, Ulrich"},{"full_name":"Tkacik, Gasper","first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455"}],"related_material":{"record":[{"id":"9869","relation":"research_data","status":"public"},{"id":"9870","status":"public","relation":"research_data"},{"id":"9871","relation":"research_data","status":"public"}]},"publication_status":"published","publisher":"Public Library of Science","department":[{"_id":"GaTk"}],"year":"2016","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).","file_date_updated":"2020-07-14T12:44:42Z","publist_id":"6050","article_number":"e0163628","language":[{"iso":"eng"}],"doi":"10.1371/journal.pone.0163628","quality_controlled":"1","project":[{"name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"month":"09"},{"citation":{"ista":"Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information in an Ising model, Public Library of Science, 10.1371/journal.pone.0163628.s002.","apa":"Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in an Ising model. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s002","ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information in an Ising model.” Public Library of Science, 2016.","ama":"Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in an Ising model. 2016. doi:10.1371/journal.pone.0163628.s002","chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of Positional Information in an Ising Model.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s002.","mla":"Hillenbrand, Patrick, et al. Computation of Positional Information in an Ising Model. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s002.","short":"P. Hillenbrand, U. Gerland, G. Tkačik, (2016)."},"doi":"10.1371/journal.pone.0163628.s002","date_published":"2016-09-27T00:00:00Z","article_processing_charge":"No","month":"09","day":"27","_id":"9870","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","year":"2016","publisher":"Public Library of Science","department":[{"_id":"GaTk"}],"title":"Computation of positional information in an Ising model","status":"public","related_material":{"record":[{"id":"1270","relation":"used_in_publication","status":"public"}]},"author":[{"full_name":"Hillenbrand, Patrick","last_name":"Hillenbrand","first_name":"Patrick"},{"first_name":"Ulrich","last_name":"Gerland","full_name":"Gerland, Ulrich"},{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","first_name":"Gašper","full_name":"Tkačik, Gašper"}],"oa_version":"Published Version","date_updated":"2023-02-21T16:56:40Z","date_created":"2021-08-10T09:23:45Z","type":"research_data_reference","abstract":[{"text":"The effect of noise in the input field on an Ising model is approximated. Furthermore, methods to compute positional information in an Ising model by transfer matrices and Monte Carlo sampling are outlined.","lang":"eng"}]},{"citation":{"ista":"Hillenbrand P, Gerland U, Tkačik G. 2016. Error bound on an estimator of position, Public Library of Science, 10.1371/journal.pone.0163628.s001.","ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Error bound on an estimator of position.” Public Library of Science, 2016.","apa":"Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Error bound on an estimator of position. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s001","ama":"Hillenbrand P, Gerland U, Tkačik G. Error bound on an estimator of position. 2016. doi:10.1371/journal.pone.0163628.s001","chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Error Bound on an Estimator of Position.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s001.","mla":"Hillenbrand, Patrick, et al. Error Bound on an Estimator of Position. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s001.","short":"P. Hillenbrand, U. Gerland, G. Tkačik, (2016)."},"date_published":"2016-09-27T00:00:00Z","doi":"10.1371/journal.pone.0163628.s001","article_processing_charge":"No","month":"09","day":"27","department":[{"_id":"GaTk"}],"publisher":"Public Library of Science","status":"public","title":"Error bound on an estimator of position","year":"2016","_id":"9869","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","oa_version":"Published Version","date_updated":"2023-02-21T16:56:40Z","date_created":"2021-08-10T08:53:48Z","related_material":{"record":[{"id":"1270","relation":"used_in_publication","status":"public"}]},"author":[{"first_name":"Patrick","last_name":"Hillenbrand","full_name":"Hillenbrand, Patrick"},{"first_name":"Ulrich","last_name":"Gerland","full_name":"Gerland, Ulrich"},{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","first_name":"Gašper","full_name":"Tkačik, Gašper"}],"type":"research_data_reference","abstract":[{"text":"A lower bound on the error of a positional estimator with limited positional information is derived.","lang":"eng"}]},{"article_processing_charge":"No","day":"27","month":"09","doi":"10.1371/journal.pone.0163628.s003","citation":{"mla":"Hillenbrand, Patrick, et al. Computation of Positional Information in a Discrete Morphogen Field. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s003.","short":"P. Hillenbrand, U. Gerland, G. Tkačik, (2016).","chicago":"Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of Positional Information in a Discrete Morphogen Field.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s003.","ama":"Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in a discrete morphogen field. 2016. doi:10.1371/journal.pone.0163628.s003","ista":"Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information in a discrete morphogen field, Public Library of Science, 10.1371/journal.pone.0163628.s003.","apa":"Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in a discrete morphogen field. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s003","ieee":"P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information in a discrete morphogen field.” Public Library of Science, 2016."},"abstract":[{"text":"The positional information in a discrete morphogen field with Gaussian noise is computed.","lang":"eng"}],"type":"research_data_reference","related_material":{"record":[{"id":"1270","relation":"used_in_publication","status":"public"}]},"author":[{"full_name":"Hillenbrand, Patrick","last_name":"Hillenbrand","first_name":"Patrick"},{"first_name":"Ulrich","last_name":"Gerland","full_name":"Gerland, Ulrich"},{"full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper","last_name":"Tkačik"}],"oa_version":"Published Version","date_updated":"2023-02-21T16:56:40Z","date_created":"2021-08-10T09:27:35Z","_id":"9871","year":"2016","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","department":[{"_id":"GaTk"}],"publisher":"Public Library of Science","status":"public","title":"Computation of positional information in a discrete morphogen field"},{"day":"01","has_accepted_license":"1","article_processing_charge":"No","date_published":"2016-08-01T00:00:00Z","page":"114","citation":{"ama":"Rieckh G. Studying the complexities of transcriptional regulation. 2016.","ista":"Rieckh G. 2016. Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria.","apa":"Rieckh, G. (2016). Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria.","ieee":"G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute of Science and Technology Austria, 2016.","mla":"Rieckh, Georg. Studying the Complexities of Transcriptional Regulation. Institute of Science and Technology Austria, 2016.","short":"G. Rieckh, Studying the Complexities of Transcriptional Regulation, Institute of Science and Technology Austria, 2016.","chicago":"Rieckh, Georg. “Studying the Complexities of Transcriptional Regulation.” Institute of Science and Technology Austria, 2016."},"abstract":[{"text":"The process of gene expression is central to the modern understanding of how cellular systems\r\nfunction. In this process, a special kind of regulatory proteins, called transcription factors,\r\nare important to determine how much protein is produced from a given gene. As biological\r\ninformation is transmitted from transcription factor concentration to mRNA levels to amounts of\r\nprotein, various sources of noise arise and pose limits to the fidelity of intracellular signaling.\r\nThis thesis concerns itself with several aspects of stochastic gene expression: (i) the mathematical\r\ndescription of complex promoters responsible for the stochastic production of biomolecules,\r\n(ii) fundamental limits to information processing the cell faces due to the interference from multiple\r\nfluctuating signals, (iii) how the presence of gene expression noise influences the evolution\r\nof regulatory sequences, (iv) and tools for the experimental study of origins and consequences\r\nof cell-cell heterogeneity, including an application to bacterial stress response systems.","lang":"eng"}],"alternative_title":["ISTA Thesis"],"type":"dissertation","oa_version":"Published Version","file":[{"relation":"main_file","file_id":"6815","checksum":"ec453918c3bf8e6f460fd1156ef7b493","date_updated":"2019-08-13T11:46:25Z","date_created":"2019-08-13T11:46:25Z","access_level":"closed","file_name":"Thesis_Georg_Rieckh_w_signature_page.pdf","content_type":"application/pdf","file_size":2614660,"creator":"dernst"},{"date_updated":"2020-09-21T11:30:40Z","date_created":"2020-09-21T11:30:40Z","checksum":"51ae398166370d18fd22478b6365c4da","success":1,"relation":"main_file","file_id":"8542","file_size":6096178,"content_type":"application/pdf","creator":"dernst","file_name":"Thesis_Georg_Rieckh.pdf","access_level":"open_access"}],"ddc":["570"],"status":"public","title":"Studying the complexities of transcriptional regulation","_id":"1128","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","month":"08","publication_identifier":{"issn":["2663-337X"]},"degree_awarded":"PhD","supervisor":[{"full_name":"Tkacik, Gasper","first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455"}],"language":[{"iso":"eng"}],"oa":1,"file_date_updated":"2020-09-21T11:30:40Z","publist_id":"6232","date_created":"2018-12-11T11:50:18Z","date_updated":"2023-09-07T11:44:34Z","author":[{"full_name":"Rieckh, Georg","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","last_name":"Rieckh","first_name":"Georg"}],"publication_status":"published","publisher":"Institute of Science and Technology Austria","department":[{"_id":"GaTk"}],"year":"2016"},{"abstract":[{"text":"Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements.","lang":"eng"}],"type":"journal_article","pubrep_id":"627","oa_version":"Published Version","file":[{"file_id":"4919","relation":"main_file","date_created":"2018-12-12T10:12:01Z","date_updated":"2020-07-14T12:44:46Z","checksum":"fe3f3a1526d180b29fe691ab11435b78","file_name":"IST-2016-627-v1+1_ncomms12307.pdf","access_level":"open_access","creator":"system","content_type":"application/pdf","file_size":861805},{"relation":"main_file","file_id":"4920","checksum":"164864a1a675f3ad80e9917c27aba07f","date_updated":"2020-07-14T12:44:46Z","date_created":"2018-12-12T10:12:02Z","access_level":"open_access","file_name":"IST-2016-627-v1+2_ncomms12307-s1.pdf","content_type":"application/pdf","file_size":1084703,"creator":"system"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1358","ddc":["576"],"status":"public","title":"Intrinsic limits to gene regulation by global crosstalk","intvolume":" 7","day":"04","has_accepted_license":"1","scopus_import":1,"date_published":"2016-08-04T00:00:00Z","publication":"Nature Communications","citation":{"ama":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307","ista":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 7, 12307.","ieee":"T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic limits to gene regulation by global crosstalk,” Nature Communications, vol. 7. Nature Publishing Group, 2016.","apa":"Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms12307","mla":"Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications, vol. 7, 12307, Nature Publishing Group, 2016, doi:10.1038/ncomms12307.","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.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms12307."},"file_date_updated":"2020-07-14T12:44:46Z","ec_funded":1,"publist_id":"5887","article_number":"12307","author":[{"id":"36A5845C-F248-11E8-B48F-1D18A9856A87","last_name":"Friedlander","first_name":"Tamar","full_name":"Friedlander, Tamar"},{"full_name":"Prizak, Roshan","first_name":"Roshan","last_name":"Prizak","id":"4456104E-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","first_name":"Calin C","full_name":"Guet, Calin C"},{"last_name":"Barton","first_name":"Nicholas H","orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H"},{"full_name":"Tkacik, Gasper","first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455"}],"related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"6071"}]},"date_created":"2018-12-11T11:51:34Z","date_updated":"2023-09-07T12:53:49Z","volume":7,"year":"2016","publication_status":"published","department":[{"_id":"GaTk"},{"_id":"NiBa"},{"_id":"CaGu"}],"publisher":"Nature Publishing Group","month":"08","doi":"10.1038/ncomms12307","language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"quality_controlled":"1","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"},{"_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation"},{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation"}]},{"type":"journal_article","abstract":[{"text":"Mathematical models are of fundamental importance in the understanding of complex population dynamics. For instance, they can be used to predict the population evolution starting from different initial conditions or to test how a system responds to external perturbations. For this analysis to be meaningful in real applications, however, it is of paramount importance to choose an appropriate model structure and to infer the model parameters from measured data. While many parameter inference methods are available for models based on deterministic ordinary differential equations, the same does not hold for more detailed individual-based models. Here we consider, in particular, stochastic models in which the time evolution of the species abundances is described by a continuous-time Markov chain. These models are governed by a master equation that is typically difficult to solve. Consequently, traditional inference methods that rely on iterative evaluation of parameter likelihoods are computationally intractable. The aim of this paper is to present recent advances in parameter inference for continuous-time Markov chain models, based on a moment closure approximation of the parameter likelihood, and to investigate how these results can help in understanding, and ultimately controlling, complex systems in ecology. Specifically, we illustrate through an agricultural pest case study how parameters of a stochastic individual-based model can be identified from measured data and how the resulting model can be used to solve an optimal control problem in a stochastic setting. In particular, we show how the matter of determining the optimal combination of two different pest control methods can be formulated as a chance constrained optimization problem where the control action is modeled as a state reset, leading to a hybrid system formulation.","lang":"eng"}],"ddc":["000","570"],"title":"Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study","status":"public","intvolume":" 3","_id":"10794","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","file":[{"date_updated":"2022-02-25T11:55:26Z","date_created":"2022-02-25T11:55:26Z","success":1,"checksum":"26c222487564e1be02a11d688d6f769d","file_id":"10795","relation":"main_file","creator":"dernst","file_size":1371201,"content_type":"application/pdf","file_name":"2015_FrontiersEnvironmScience_Parise.pdf","access_level":"open_access"}],"keyword":["General Environmental Science"],"scopus_import":"1","day":"10","article_processing_charge":"No","has_accepted_license":"1","article_type":"original","publication":"Frontiers in Environmental Science","citation":{"chicago":"Parise, Francesca, John Lygeros, and Jakob Ruess. “Bayesian Inference for Stochastic Individual-Based Models of Ecological Systems: A Pest Control Simulation Study.” Frontiers in Environmental Science. Frontiers, 2015. https://doi.org/10.3389/fenvs.2015.00042.","mla":"Parise, Francesca, et al. “Bayesian Inference for Stochastic Individual-Based Models of Ecological Systems: A Pest Control Simulation Study.” Frontiers in Environmental Science, vol. 3, 42, Frontiers, 2015, doi:10.3389/fenvs.2015.00042.","short":"F. Parise, J. Lygeros, J. Ruess, Frontiers in Environmental Science 3 (2015).","ista":"Parise F, Lygeros J, Ruess J. 2015. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 3, 42.","apa":"Parise, F., Lygeros, J., & Ruess, J. (2015). Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. Frontiers. https://doi.org/10.3389/fenvs.2015.00042","ieee":"F. Parise, J. Lygeros, and J. Ruess, “Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study,” Frontiers in Environmental Science, vol. 3. Frontiers, 2015.","ama":"Parise F, Lygeros J, Ruess J. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 2015;3. doi:10.3389/fenvs.2015.00042"},"date_published":"2015-06-10T00:00:00Z","article_number":"42","file_date_updated":"2022-02-25T11:55:26Z","ec_funded":1,"publication_status":"published","department":[{"_id":"ToHe"},{"_id":"GaTk"}],"publisher":"Frontiers","acknowledgement":"The authors would like to acknowledge contributions from Baptiste Mottet who performed preliminary analysis regarding parameter inference for the considered case study in a student project (Mottet, 2014/2015).\r\nThe 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] and from SystemsX under the project SignalX.","year":"2015","date_created":"2022-02-25T11:42:25Z","date_updated":"2022-02-25T11:59:23Z","volume":3,"author":[{"last_name":"Parise","first_name":"Francesca","full_name":"Parise, Francesca"},{"full_name":"Lygeros, John","first_name":"John","last_name":"Lygeros"},{"last_name":"Ruess","first_name":"Jakob","orcid":"0000-0003-1615-3282","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","full_name":"Ruess, Jakob"}],"month":"06","publication_identifier":{"issn":["2296-665X"]},"quality_controlled":"1","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"language":[{"iso":"eng"}],"doi":"10.3389/fenvs.2015.00042"},{"month":"12","oa":1,"quality_controlled":"1","project":[{"grant_number":"267989","_id":"25EE3708-B435-11E9-9278-68D0E5697425","name":"Quantitative Reactive Modeling","call_identifier":"FP7"},{"_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","call_identifier":"FWF"},{"grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","name":"The Wittgenstein Prize","call_identifier":"FWF"},{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"}],"doi":"10.1063/1.4937937","language":[{"iso":"eng"}],"article_number":"244103","file_date_updated":"2020-07-14T12:45:01Z","ec_funded":1,"publist_id":"5632","year":"2015","publication_status":"published","department":[{"_id":"ToHe"},{"_id":"GaTk"}],"publisher":"American Institute of Physics","author":[{"first_name":"Jakob","last_name":"Ruess","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1615-3282","full_name":"Ruess, Jakob"}],"date_updated":"2021-01-12T06:51:28Z","date_created":"2018-12-11T11:52:36Z","volume":143,"scopus_import":1,"day":"22","has_accepted_license":"1","publication":"Journal of Chemical Physics","citation":{"ama":"Ruess J. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 2015;143(24). doi:10.1063/1.4937937","ista":"Ruess J. 2015. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 143(24), 244103.","apa":"Ruess, J. (2015). Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. American Institute of Physics. https://doi.org/10.1063/1.4937937","ieee":"J. Ruess, “Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space,” Journal of Chemical Physics, vol. 143, no. 24. American Institute of Physics, 2015.","mla":"Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics, vol. 143, no. 24, 244103, American Institute of Physics, 2015, doi:10.1063/1.4937937.","short":"J. Ruess, Journal of Chemical Physics 143 (2015).","chicago":"Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics. American Institute of Physics, 2015. https://doi.org/10.1063/1.4937937."},"date_published":"2015-12-22T00:00:00Z","type":"journal_article","abstract":[{"lang":"eng","text":"Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space. "}],"issue":"24","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1539","title":"Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space","ddc":["000"],"status":"public","intvolume":" 143","pubrep_id":"593","oa_version":"Published Version","file":[{"access_level":"open_access","file_name":"IST-2016-593-v1+1_Minimal_moment_equations.pdf","content_type":"application/pdf","file_size":605355,"creator":"system","relation":"main_file","file_id":"4641","checksum":"838657118ae286463a2b7737319f35ce","date_created":"2018-12-12T10:07:43Z","date_updated":"2020-07-14T12:45:01Z"}]},{"day":"30","scopus_import":1,"date_published":"2015-06-30T00:00:00Z","publication":"PNAS","citation":{"mla":"Ruess, Jakob, et al. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS, vol. 112, no. 26, National Academy of Sciences, 2015, pp. 8148–53, doi:10.1073/pnas.1423947112.","short":"J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, J. Lygeros, PNAS 112 (2015) 8148–8153.","chicago":"Ruess, Jakob, Francesca Parise, Andreas Milias Argeitis, Mustafa Khammash, and John Lygeros. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1423947112.","ama":"Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 2015;112(26):8148-8153. doi:10.1073/pnas.1423947112","ista":"Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. 2015. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 112(26), 8148–8153.","apa":"Ruess, J., Parise, F., Milias Argeitis, A., Khammash, M., & Lygeros, J. (2015). Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1423947112","ieee":"J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, and J. Lygeros, “Iterative experiment design guides the characterization of a light-inducible gene expression circuit,” PNAS, vol. 112, no. 26. National Academy of Sciences, pp. 8148–8153, 2015."},"page":"8148 - 8153","abstract":[{"text":"Systems biology rests on the idea that biological complexity can be better unraveled through the interplay of modeling and experimentation. However, the success of this approach depends critically on the informativeness of the chosen experiments, which is usually unknown a priori. Here, we propose a systematic scheme based on iterations of optimal experiment design, flow cytometry experiments, and Bayesian parameter inference to guide the discovery process in the case of stochastic biochemical reaction networks. To illustrate the benefit of our methodology, we apply it to the characterization of an engineered light-inducible gene expression circuit in yeast and compare the performance of the resulting model with models identified from nonoptimal experiments. In particular, we compare the parameter posterior distributions and the precision to which the outcome of future experiments can be predicted. Moreover, we illustrate how the identified stochastic model can be used to determine light induction patterns that make either the average amount of protein or the variability in a population of cells follow a desired profile. Our results show that optimal experiment design allows one to derive models that are accurate enough to precisely predict and regulate the protein expression in heterogeneous cell populations over extended periods of time.","lang":"eng"}],"issue":"26","type":"journal_article","oa_version":"Submitted Version","_id":"1538","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","title":"Iterative experiment design guides the characterization of a light-inducible gene expression circuit","intvolume":" 112","month":"06","doi":"10.1073/pnas.1423947112","language":[{"iso":"eng"}],"oa":1,"external_id":{"pmid":["26085136"]},"main_file_link":[{"open_access":"1","url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491780/"}],"quality_controlled":"1","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"publist_id":"5633","ec_funded":1,"author":[{"orcid":"0000-0003-1615-3282","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","last_name":"Ruess","first_name":"Jakob","full_name":"Ruess, Jakob"},{"full_name":"Parise, Francesca","first_name":"Francesca","last_name":"Parise"},{"full_name":"Milias Argeitis, Andreas","last_name":"Milias Argeitis","first_name":"Andreas"},{"last_name":"Khammash","first_name":"Mustafa","full_name":"Khammash, Mustafa"},{"full_name":"Lygeros, John","last_name":"Lygeros","first_name":"John"}],"date_created":"2018-12-11T11:52:36Z","date_updated":"2021-01-12T06:51:27Z","volume":112,"acknowledgement":"J.R., F.P., and J.L. acknowledge support from the European Commission under the Network of Excellence HYCON2 (highly-complex and networked control systems) and SystemsX.ch under the SignalX Project. J.R. acknowledges support from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013 under REA (Research Executive Agency) Grant 291734. M.K. acknowledges support from Human Frontier Science Program Grant RP0061/2011 (www.hfsp.org). ","year":"2015","pmid":1,"publication_status":"published","department":[{"_id":"ToHe"},{"_id":"GaTk"}],"publisher":"National Academy of Sciences"},{"article_number":"145","file_date_updated":"2020-07-14T12:45:02Z","publist_id":"5607","ec_funded":1,"year":"2015","publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Frontiers Research Foundation","author":[{"last_name":"Gilson","first_name":"Matthieu","full_name":"Gilson, Matthieu"},{"first_name":"Cristina","last_name":"Savin","id":"3933349E-F248-11E8-B48F-1D18A9856A87","full_name":"Savin, Cristina"},{"full_name":"Zenke, Friedemann","last_name":"Zenke","first_name":"Friedemann"}],"date_created":"2018-12-11T11:52:45Z","date_updated":"2021-01-12T06:51:37Z","volume":9,"month":"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","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"quality_controlled":"1","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"doi":"10.3389/fncom.2015.00145","language":[{"iso":"eng"}],"type":"journal_article","issue":"11","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1564","title":"Editorial: Emergent neural computation from the interaction of different forms of plasticity","status":"public","ddc":["570"],"intvolume":" 9","pubrep_id":"479","file":[{"access_level":"open_access","file_name":"IST-2016-479-v1+1_fncom-09-00145.pdf","creator":"system","content_type":"application/pdf","file_size":187038,"file_id":"4927","relation":"main_file","checksum":"cea73b6d3ef1579f32da10b82f4de4fd","date_created":"2018-12-12T10:12:09Z","date_updated":"2020-07-14T12:45:02Z"}],"oa_version":"Published Version","scopus_import":1,"day":"30","has_accepted_license":"1","publication":"Frontiers in Computational Neuroscience","citation":{"ista":"Gilson M, Savin C, Zenke F. 2015. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 9(11), 145.","apa":"Gilson, M., Savin, C., & Zenke, F. (2015). Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2015.00145","ieee":"M. Gilson, C. Savin, and F. Zenke, “Editorial: Emergent neural computation from the interaction of different forms of plasticity,” Frontiers in Computational Neuroscience, vol. 9, no. 11. Frontiers Research Foundation, 2015.","ama":"Gilson M, Savin C, Zenke F. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 2015;9(11). doi:10.3389/fncom.2015.00145","chicago":"Gilson, Matthieu, Cristina Savin, and Friedemann Zenke. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience. Frontiers Research Foundation, 2015. https://doi.org/10.3389/fncom.2015.00145.","mla":"Gilson, Matthieu, et al. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience, vol. 9, no. 11, 145, Frontiers Research Foundation, 2015, doi:10.3389/fncom.2015.00145.","short":"M. Gilson, C. Savin, F. Zenke, Frontiers in Computational Neuroscience 9 (2015)."},"date_published":"2015-11-30T00:00:00Z"}]