Loïc Paulevé: Symbolic learning of ensembles of Boolean networks predictive for cell fate decision

In this talk, I’ll give a global overview of challenges related to the learning of dynamical models of cellular differentiation processes. I’ll present on-going work mixing formal methods for modelling dynamical systems and model synthesis from constraints on expected emerging behaviors. This will be illustrated in the scope of the synthesis and analysis of ensembles of Boolean automata networks using Answer-Set Programming from data relating to the structure of the network and observations of the system.