Most Permissive Boolean Networks with Loïc Paulevé

In systems biology, Boolean networks are a way to model interactions such as

gene regulation or cell signaling. The standard

interpretations of Boolean networks are the synchronous, asynchronous, and

fully asynchronous semantics.

In this episode, Loïc Paulevé explains how the

same Boolean networks can be interpreted in a new, “most permissive” way.

Loïc proved mathematically that his semantics can reproduce all behaviors

achievable by a compatible quantitative model, whereas the

traditional interpretations in general cannot. Furthermore, it turns out that

deciding whether a certain state in a Boolean network is reachable can be done

much more efficiently in MPBNs than in the traditional interpretations.

Links:

Reconciling Qualitative, Abstract, and Scalable Modeling of Biological Networks (Loïc Paulevé, Juraj Kolčák, Thomas Chatain, Stefan Haar)

mpbn on GitHub: an implementation of reachability and attractor analysis in Most Permissive Boolean Networks

BoNesis on GitHub: synthesis of Most Permissive Boolean Networks from network architecture and dynamical properties

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