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.
- 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