{"ec_funded":1,"month":"03","project":[{"_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","name":"IST-BRIDGE: International postdoctoral program","call_identifier":"H2020","grant_number":"101034413"}],"page":"10714-10722","scopus_import":"1","acknowledgement":"This work was supported by Institut Carnot STAR, Marseille, France and by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101034413.","article_processing_charge":"No","issue":"9","intvolume":"        38","publication_identifier":{"isbn":["1577358872"],"issn":["2159-5399"],"eissn":["2374-3468"]},"_id":"15321","quality_controlled":"1","oa_version":"Published Version","publisher":"Association for the Advancement of Artificial Intelligence","main_file_link":[{"url":"https://amu.hal.science/hal-04523118/","open_access":"1"}],"author":[{"last_name":"Trinh","first_name":"Giang","full_name":"Trinh, Giang"},{"full_name":"Benhamou, Belaid","first_name":"Belaid","last_name":"Benhamou"},{"orcid":"0000-0003-1993-0331","full_name":"Pastva, Samuel","first_name":"Samuel","id":"07c5ea74-f61c-11ec-a664-aa7c5d957b2b","last_name":"Pastva"},{"last_name":"Soliman","first_name":"Sylvain","full_name":"Soliman, Sylvain"}],"date_published":"2024-03-25T00:00:00Z","type":"conference","abstract":[{"text":"Boolean Networks (BNs) are widely used as a modeling formalism in several domains, notably systems biology and computer science. A fundamental problem in BN analysis is the enumeration of trap spaces, which are hypercubes in the state space that cannot be escaped once entered. Several methods have been proposed for enumerating trap spaces, however they often suffer from scalability and efficiency issues, particularly for large and complex models. To our knowledge, the most efficient and recent methods for the trap space enumeration all rely on Answer Set Programming (ASP), which has been widely applied to the analysis of BNs. Motivated by these considerations, our work proposes a new method for enumerating trap spaces in BNs using ASP. We evaluate the method on a mix of 250+ real-world and 400+ randomly generated BNs, showing that it enables analysis of models beyond the capabilities of existing tools (namely pyboolnet, mpbn, trappist, and trapmvn).","lang":"eng"}],"volume":38,"oa":1,"publication":"Proceedings of the 38th AAAI Conference on Artificial Intelligence","date_created":"2024-04-14T22:01:02Z","department":[{"_id":"ToHe"}],"citation":{"apa":"Trinh, G., Benhamou, B., Pastva, S., &#38; Soliman, S. (2024). Scalable enumeration of trap spaces in boolean networks via answer set programming. In <i>Proceedings of the 38th AAAI Conference on Artificial Intelligence</i> (Vol. 38, pp. 10714–10722). Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v38i9.28943\">https://doi.org/10.1609/aaai.v38i9.28943</a>","ieee":"G. Trinh, B. Benhamou, S. Pastva, and S. Soliman, “Scalable enumeration of trap spaces in boolean networks via answer set programming,” in <i>Proceedings of the 38th AAAI Conference on Artificial Intelligence</i>, 2024, vol. 38, no. 9, pp. 10714–10722.","ista":"Trinh G, Benhamou B, Pastva S, Soliman S. 2024. Scalable enumeration of trap spaces in boolean networks via answer set programming. Proceedings of the 38th AAAI Conference on Artificial Intelligence. vol. 38, 10714–10722.","chicago":"Trinh, Giang, Belaid Benhamou, Samuel Pastva, and Sylvain Soliman. “Scalable Enumeration of Trap Spaces in Boolean Networks via Answer Set Programming.” In <i>Proceedings of the 38th AAAI Conference on Artificial Intelligence</i>, 38:10714–22. Association for the Advancement of Artificial Intelligence, 2024. <a href=\"https://doi.org/10.1609/aaai.v38i9.28943\">https://doi.org/10.1609/aaai.v38i9.28943</a>.","short":"G. Trinh, B. Benhamou, S. Pastva, S. Soliman, in:, Proceedings of the 38th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2024, pp. 10714–10722.","mla":"Trinh, Giang, et al. “Scalable Enumeration of Trap Spaces in Boolean Networks via Answer Set Programming.” <i>Proceedings of the 38th AAAI Conference on Artificial Intelligence</i>, vol. 38, no. 9, Association for the Advancement of Artificial Intelligence, 2024, pp. 10714–22, doi:<a href=\"https://doi.org/10.1609/aaai.v38i9.28943\">10.1609/aaai.v38i9.28943</a>.","ama":"Trinh G, Benhamou B, Pastva S, Soliman S. Scalable enumeration of trap spaces in boolean networks via answer set programming. In: <i>Proceedings of the 38th AAAI Conference on Artificial Intelligence</i>. Vol 38. Association for the Advancement of Artificial Intelligence; 2024:10714-10722. doi:<a href=\"https://doi.org/10.1609/aaai.v38i9.28943\">10.1609/aaai.v38i9.28943</a>"},"status":"public","language":[{"iso":"eng"}],"date_updated":"2024-04-17T08:35:24Z","publication_status":"published","doi":"10.1609/aaai.v38i9.28943","day":"25","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Scalable enumeration of trap spaces in boolean networks via answer set programming","year":"2024"}