{"tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"date_published":"2017-12-01T00:00:00Z","publication_identifier":{"issn":["00015903"]},"date_updated":"2023-09-20T11:06:03Z","date_created":"2018-12-11T11:51:32Z","author":[{"id":"3444EA5E-F248-11E8-B48F-1D18A9856A87","first_name":"Mirco","full_name":"Giacobbe, Mirco","orcid":"0000-0001-8180-0904","last_name":"Giacobbe"},{"first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C","last_name":"Guet"},{"first_name":"Ashutosh","id":"335E5684-F248-11E8-B48F-1D18A9856A87","full_name":"Gupta, Ashutosh","last_name":"Gupta"},{"first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000−0002−2985−7724","full_name":"Henzinger, Thomas A","last_name":"Henzinger"},{"full_name":"Paixao, Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","first_name":"Tiago","last_name":"Paixao"},{"full_name":"Petrov, Tatjana","orcid":"0000-0002-9041-0905","id":"3D5811FC-F248-11E8-B48F-1D18A9856A87","first_name":"Tatjana","last_name":"Petrov"}],"type":"journal_article","quality_controlled":"1","oa":1,"issue":"8","scopus_import":"1","publist_id":"5898","day":"01","external_id":{"isi":["000414343200003"]},"has_accepted_license":"1","intvolume":"        54","pubrep_id":"649","article_processing_charge":"No","_id":"1351","year":"2017","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 logic. 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."}],"title":"Model checking the evolution of gene regulatory networks","isi":1,"month":"12","doi":"10.1007/s00236-016-0278-x","related_material":{"record":[{"relation":"earlier_version","status":"public","id":"1835"}]},"oa_version":"Published Version","department":[{"_id":"ToHe"},{"_id":"CaGu"},{"_id":"NiBa"}],"publication":"Acta Informatica","status":"public","project":[{"grant_number":"267989","_id":"25EE3708-B435-11E9-9278-68D0E5697425","name":"Quantitative Reactive Modeling","call_identifier":"FP7"},{"call_identifier":"FWF","name":"Rigorous Systems Engineering","_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23"},{"name":"The Wittgenstein Prize","call_identifier":"FWF","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211"},{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation"},{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"},{"_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7"}],"citation":{"short":"M. Giacobbe, C.C. Guet, A. Gupta, T.A. Henzinger, T. Paixao, T. Petrov, Acta Informatica 54 (2017) 765–787.","mla":"Giacobbe, Mirco, et al. “Model Checking the Evolution of Gene Regulatory Networks.” <i>Acta Informatica</i>, vol. 54, no. 8, Springer, 2017, pp. 765–87, doi:<a href=\"https://doi.org/10.1007/s00236-016-0278-x\">10.1007/s00236-016-0278-x</a>.","apa":"Giacobbe, M., Guet, C. C., Gupta, A., Henzinger, T. A., Paixao, T., &#38; Petrov, T. (2017). Model checking the evolution of gene regulatory networks. <i>Acta Informatica</i>. Springer. <a href=\"https://doi.org/10.1007/s00236-016-0278-x\">https://doi.org/10.1007/s00236-016-0278-x</a>","ista":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. 2017. Model checking the evolution of gene regulatory networks. Acta Informatica. 54(8), 765–787.","ieee":"M. Giacobbe, C. C. Guet, A. Gupta, T. A. Henzinger, T. Paixao, and T. Petrov, “Model checking the evolution of gene regulatory networks,” <i>Acta Informatica</i>, vol. 54, no. 8. Springer, pp. 765–787, 2017.","chicago":"Giacobbe, Mirco, Calin C Guet, Ashutosh Gupta, Thomas A Henzinger, Tiago Paixao, and Tatjana Petrov. “Model Checking the Evolution of Gene Regulatory Networks.” <i>Acta Informatica</i>. Springer, 2017. <a href=\"https://doi.org/10.1007/s00236-016-0278-x\">https://doi.org/10.1007/s00236-016-0278-x</a>.","ama":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. Model checking the evolution of gene regulatory networks. <i>Acta Informatica</i>. 2017;54(8):765-787. doi:<a href=\"https://doi.org/10.1007/s00236-016-0278-x\">10.1007/s00236-016-0278-x</a>"},"publication_status":"published","page":"765 - 787","publisher":"Springer","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","ec_funded":1,"language":[{"iso":"eng"}],"volume":54,"file_date_updated":"2020-07-14T12:44:46Z","ddc":["006","576"],"file":[{"date_created":"2019-01-17T15:57:29Z","date_updated":"2020-07-14T12:44:46Z","file_id":"5841","creator":"dernst","file_size":755241,"file_name":"2017_ActaInformatica_Giacobbe.pdf","relation":"main_file","checksum":"4e661d9135d7f8c342e8e258dee76f3e","content_type":"application/pdf","access_level":"open_access"}]}