BNClassifier: Classifying boolean models by dynamic properties LNBI Beneš, Nikola Brim, Luboš Huvar, Ondřej Pastva, Samuel ; https://orcid.org/0000-0003-1993-0331 Šafránek, David 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. Springer Nature 2024 info:eu-repo/semantics/conferenceObject doc-type:ConferenceObject ConferenceObject http://purl.org/coar/resource_type/c_5794 https://research-explorer.ista.ac.at/record/18177 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> eng info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-031-71671-3_2 info:eu-repo/semantics/altIdentifier/issn/0302-9743 info:eu-repo/semantics/altIdentifier/e-issn/1611-3349 info:eu-repo/semantics/altIdentifier/isbn/9783031716706 info:eu-repo/semantics/altIdentifier/wos/001333144400002 info:eu-repo/semantics/closedAccess