{"citation":{"ieee":"M. Giacobbe, C. C. Guet, A. Gupta, T. A. Henzinger, T. Paixao, and T. Petrov, “Model checking gene regulatory networks,” vol. 9035. Springer, pp. 469–483, 2015.","mla":"Giacobbe, Mirco, et al. <i>Model Checking Gene Regulatory Networks</i>. Vol. 9035, Springer, 2015, pp. 469–83, doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">10.1007/978-3-662-46681-0_47</a>.","short":"M. Giacobbe, C.C. Guet, A. Gupta, T.A. Henzinger, T. Paixao, T. Petrov, 9035 (2015) 469–483.","apa":"Giacobbe, M., Guet, C. C., Gupta, A., Henzinger, T. A., Paixao, T., &#38; Petrov, T. (2015). Model checking gene regulatory networks. Presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">https://doi.org/10.1007/978-3-662-46681-0_47</a>","ista":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. 2015. Model checking gene regulatory networks. 9035, 469–483.","chicago":"Giacobbe, Mirco, Calin C Guet, Ashutosh Gupta, Thomas A Henzinger, Tiago Paixao, and Tatjana Petrov. “Model Checking Gene Regulatory Networks.” Lecture Notes in Computer Science. Springer, 2015. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">https://doi.org/10.1007/978-3-662-46681-0_47</a>.","ama":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. Model checking gene regulatory networks. 2015;9035:469-483. doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">10.1007/978-3-662-46681-0_47</a>"},"conference":{"name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems","start_date":"2015-04-11","location":"London, United Kingdom","end_date":"2015-04-18"},"ec_funded":1,"_id":"1835","language":[{"iso":"eng"}],"author":[{"first_name":"Mirco","last_name":"Giacobbe","full_name":"Giacobbe, Mirco","id":"3444EA5E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8180-0904"},{"full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C","last_name":"Guet","orcid":"0000-0001-6220-2052"},{"id":"335E5684-F248-11E8-B48F-1D18A9856A87","full_name":"Gupta, Ashutosh","first_name":"Ashutosh","last_name":"Gupta"},{"first_name":"Thomas A","last_name":"Henzinger","full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000−0002−2985−7724"},{"last_name":"Paixao","first_name":"Tiago","full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953"},{"orcid":"0000-0002-9041-0905","first_name":"Tatjana","last_name":"Petrov","id":"3D5811FC-F248-11E8-B48F-1D18A9856A87","full_name":"Petrov, Tatjana"}],"page":"469 - 483","doi":"10.1007/978-3-662-46681-0_47","acknowledgement":"SNSF Early Postdoc.Mobility Fellowship, the grant number P2EZP2 148797.\r\n","project":[{"call_identifier":"FP7","grant_number":"267989","_id":"25EE3708-B435-11E9-9278-68D0E5697425","name":"Quantitative Reactive Modeling"},{"name":"Rigorous Systems Engineering","_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23","call_identifier":"FWF"},{"call_identifier":"FWF","grant_number":"Z211","name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FP7","grant_number":"618091","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"},{"call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme"}],"intvolume":"      9035","publist_id":"5267","volume":9035,"year":"2015","publication_status":"published","date_published":"2015-04-01T00:00:00Z","department":[{"_id":"ToHe"},{"_id":"CaGu"},{"_id":"NiBa"}],"abstract":[{"lang":"eng","text":"The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs –an important problem of interest in evolutionary biology– more efficiently than the classical simulation method. We specify the property in linear temporal logics. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights."}],"main_file_link":[{"url":"http://arxiv.org/abs/1410.7704","open_access":"1"}],"type":"conference","day":"01","month":"04","date_updated":"2023-09-20T11:06:03Z","title":"Model checking gene regulatory networks","quality_controlled":"1","status":"public","related_material":{"record":[{"status":"public","relation":"later_version","id":"1351"}]},"alternative_title":["LNCS"],"oa_version":"Preprint","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2018-12-11T11:54:16Z","series_title":"Lecture Notes in Computer Science","publisher":"Springer","scopus_import":1}