Bayesian inference of causality in gene regulatory networks

schedule le mercredi 23 mai 2018 de 17h00 à 18h00

Organisé par : GTT

Intervenant : Flaminia Zane (LPSM)
Lieu : salle Paul Levy

Sujet : Bayesian inference of causality in gene regulatory networks

Résumé :

From a soil bacterium to the colleague sitting next to us in our office, every living organism is a complex system shaped by genome regulation mechanisms and interaction with the environment. The technological advances experienced during the last decade in biological research have led to the production of an incredible amount of data and completely changed the way we approach biological problems of interest. Data integration and mathematical models are needed to make sense out of all the data we are now able to produce. Bayesian statistics has been widely used in the past few years for learning about biological models. In this context, we will see how we can infer causality in genetic interactions, using Bayesian networks as a model.  Such an approach is promising for going deeper into the mechanisms that regulate life and that, when disrupted, lead eventually to complex diseases like cancer.