Predictive Boolean Network Ensembles

Research project funded by ANR (French National Research Agency; grant ANR-20-CE45-0001).

Bridging the gap between dynamical systems and their partial observation, computational models of biological processes aim at uncovering key mechanisms driving cellular dynamics, and ultimately predict their behaviour under unobserved conditions. The BNeDiction project aims at providing a general methodology for making predictions from data on systems structure and dynamics by the means of ensembles of Boolean networks, an unexplored direction. Based on recent advances on the symbolic and implicit formal characterization of the compatible models using logic programming, the key challenges relate to the sampling of ensemble of diverse models, and the evaluation and maximization of its predictive power. Overall, the project aspires at delivering a convincing methodology for assessing the adequacy of automated logical modelling from experimental data, a key and recurring question at the intersection of artificial intelligence and life sciences.

Principal investigator: Loïc Paulevé (CNRS, LaBRI, Bordeaux, France)


If you are candidate for a research internship, PhD, or post-doc and interested in at least one of the following topic, contact me!

Si vous cherchez un stage de recherche, un sujet de thèse, ou un projet de post-doc, et que vous êtes intéressé par un des sujets suivants, contactez moi!

Voici quelques exemples de sujets qui peuvent se décliner en stages de Master (voire L3), thèse de doctorat, ou projet de post-doctorat :

Stage - Synthèse et apprentissage de réseaux booléens prédictifs pour la différenciation cellulaire
#MachineLearning #BioInformatics #LogicProgramming #Python

Stage - Synthèse de réseaux booléens par résolution de problèmes de satisfiabilité avec quantificateurs
#SAT #QBF #Logic #DynamicalSystems

Stage - Implémentation en Julia d’un simulateur de réseaux booléens
#Programming #Simulations #HighPerformance