Séminaires
Séminaire du 23 mars 2018
Lieu
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
Programme
14h00-15h00: Serena Cerrito (IBISC)
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.
15h00-15h30 : Célia Biane (IBISC)
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.