{"volume":14971,"language":[{"iso":"eng"}],"quality_controlled":"1","day":"19","_id":"18177","date_created":"2024-10-06T22:01:12Z","intvolume":"     14971","date_updated":"2024-10-07T10:56:29Z","author":[{"first_name":"Nikola","full_name":"Beneš, Nikola","last_name":"Beneš"},{"first_name":"Luboš","full_name":"Brim, Luboš","last_name":"Brim"},{"first_name":"Ondřej","full_name":"Huvar, Ondřej","last_name":"Huvar"},{"orcid":"0000-0003-1993-0331","full_name":"Pastva, Samuel","last_name":"Pastva","id":"07c5ea74-f61c-11ec-a664-aa7c5d957b2b","first_name":"Samuel"},{"first_name":"David","last_name":"Šafránek","full_name":"Šafránek, David"}],"acknowledgement":"The work has been supported by the Czech Science Foundation grant No. GA22-10845S. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 101034413.","department":[{"_id":"ToHe"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","title":"BNClassifier: Classifying boolean models by dynamic properties","oa_version":"None","scopus_import":"1","page":"19-26","month":"09","alternative_title":["LNBI"],"status":"public","abstract":[{"text":"Partially Specified Boolean Networks (PSBNs) represent a family of Boolean models resulting from possible interpretations of unknown update logics. Hybrid extension of CTL (HCTL) has the power to express complex dynamical phenomena, such as oscillations or stability. We present BNClassifier to classify Boolean Networks corresponding to a given PSBN according to criteria specified in HCTL. The implementation of the tool is fully symbolic (based on BDDs). The results are visualised using the machine-learning-based technology of decision trees.","lang":"eng"}],"citation":{"apa":"Beneš, N., Brim, L., Huvar, O., Pastva, S., &#38; Šafránek, D. (2024). BNClassifier: Classifying boolean models by dynamic properties. In <i>Computational Methods in Systems Biology</i> (Vol. 14971, pp. 19–26). Springer Nature. <a href=\"https://doi.org/10.1007/978-3-031-71671-3_2\">https://doi.org/10.1007/978-3-031-71671-3_2</a>","ista":"Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. 2024. BNClassifier: Classifying boolean models by dynamic properties. Computational Methods in Systems Biology. , LNBI, vol. 14971, 19–26.","ieee":"N. Beneš, L. Brim, O. Huvar, S. Pastva, and D. Šafránek, “BNClassifier: Classifying boolean models by dynamic properties,” in <i>Computational Methods in Systems Biology</i>, 2024, vol. 14971, pp. 19–26.","mla":"Beneš, Nikola, et al. “BNClassifier: Classifying Boolean Models by Dynamic Properties.” <i>Computational Methods in Systems Biology</i>, vol. 14971, Springer Nature, 2024, pp. 19–26, doi:<a href=\"https://doi.org/10.1007/978-3-031-71671-3_2\">10.1007/978-3-031-71671-3_2</a>.","short":"N. Beneš, L. Brim, O. Huvar, S. Pastva, D. Šafránek, in:, Computational Methods in Systems Biology, Springer Nature, 2024, pp. 19–26.","ama":"Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. BNClassifier: Classifying boolean models by dynamic properties. In: <i>Computational Methods in Systems Biology</i>. Vol 14971. Springer Nature; 2024:19-26. doi:<a href=\"https://doi.org/10.1007/978-3-031-71671-3_2\">10.1007/978-3-031-71671-3_2</a>","chicago":"Beneš, Nikola, Luboš Brim, Ondřej Huvar, Samuel Pastva, and David Šafránek. “BNClassifier: Classifying Boolean Models by Dynamic Properties.” In <i>Computational Methods in Systems Biology</i>, 14971:19–26. Springer Nature, 2024. <a href=\"https://doi.org/10.1007/978-3-031-71671-3_2\">https://doi.org/10.1007/978-3-031-71671-3_2</a>."},"doi":"10.1007/978-3-031-71671-3_2","publication":"Computational Methods in Systems Biology","type":"conference","year":"2024","publication_identifier":{"issn":["0302-9743"],"isbn":["9783031716706"],"eissn":["1611-3349"]},"date_published":"2024-09-19T00:00:00Z","ec_funded":1,"publisher":"Springer Nature","project":[{"grant_number":"101034413","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","name":"IST-BRIDGE: International postdoctoral program","call_identifier":"H2020"}],"article_processing_charge":"No"}