BNClassifier: Classifying Boolean Models by Dynamic Properties

• Autoři: BENEŠ Nikola; BRIM Luboš; HUVAR Ondřej; PASTVA Samuel; ŠAFRÁNEK David
• Rok publikování: 2024
• Druh: Článek ve sborníku
• Konference: Computational Methods in Systems Biology
• Fakulta / Pracoviště MU: Fakulta informatiky
• www: https://link.springer.com/chapter/10.1007/978-3-031-71671-3_2
• Doi: http://dx.doi.org/10.1007/978-3-031-71671-3_2
• Klíčová slova: Boolean Network; Model Checking; Hybrid Logic

Přiložené soubory

• cmsb2024.pdf

• Popis: 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 visualized using the machine-learning-based technology of decision trees.

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