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

gene regulation or cell signaling. The standardinterpretations of Boolean networks are the synchronous, asynchronous, andfully 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 behaviorsachievable by a compatible quantitative model, whereas thetraditional interpretations in general cannot. Furthermore, it turns out thatdeciding whether a certain state in a Boolean network is reachable can be donemuch 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