laboratoire IBISC, bat. IBGBI, 23 bd de France, Evry, Salle de réunion 3ème étage: comment y aller
Il est possible de garer sa voiture dans le parking souterrain en appelant la loge à partir de la borne d'entrée
Abstract : Minimization of ATL* Models with Respect to Bisimulation The aim of this work is to provide a general method to minimize the size (number of states) of a model M of an ATL* formula. Our approach is founded on the notion of alternating bisimulation: given a model M, it is transformed in a stepwise manner into a new model M' minimal with respect to bisimulation. The method has been implemented and will be integrated into the prover TATL, that constructively decides satisfiability of an ATL* formula by building a tableau from which, when open, models of the input formula can be extracted.
Abstract :Abduction based drug target discovery using Boolean control network Network medicine aims at redefining disease at the biological networks level in order to provide a better understanding of the causal mechanisms at stake during disease progression. Studies in this field have shown that behavioral reprogramming observed in complex diseases such as Cancer is caused by molecular network rewiring. Currently, most computational approaches rely on simulations to relate molecular network perturbations to their phenotypic effect. However, few computational methods are available for inferring the molecular perturbations responsible for an observed phenotype. During this presentation, I will, first, introduce Boolean Control Networks that constitute a formalism for expressing network rewiring, then, I will specify two modalities of dynamical network reprogramming and present an abduction-based algorithm enabling the inference of the causal perturbations leading to expected dynamical behaviors. Finally, I will show an application of this theoretical approach to the inference of causal genes in breast cancer and the prediction of new molecular targets for drugs.