Variable Stabilisation in Boolean Monotonic Model Pools
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Proceedings |
| Conference | Computational Methods in Systems Biology |
| MU Faculty or unit | |
| Citation | |
| Web | https://link.springer.com/chapter/10.1007/978-3-031-15034-0_6 |
| Doi | http://dx.doi.org/10.1007/978-3-031-15034-0_6 |
| Keywords | boolean network; monotonic function; influence graph |
| Attached files | |
| Description | One of the central issues in logical modeling is whether a certain property of the model emerges due to its topological structure (i.e. its influence graph), or due to its dynamical structure (i.e. its logical update functions). In this paper, we practically evaluate a previously proposed formal instrument for studying this question: monotonic model pools and their associated skeleton Boolean networks. Specifically, we propose a simplified over-approximation theorem for skeleton networks and study the emergence of variable stability in these systems. Additionally, we consider the notion of minimal stabilizing interventions and show how to compute such interventions symbolically. We survey the practicality of this methodology on 100+ real-world Boolean networks. |
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