Publication details
BNClassifier: Classifying Boolean Models by Dynamic Properties
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Article in Proceedings |
| Conference | Computational Methods in Systems Biology |
| MU Faculty or unit | |
| Citation | |
| web | 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 |
| Keywords | Boolean Network; Model Checking; Hybrid Logic |
| Attached files | |
| Description | 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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