talk 'Machine learning for precision medicine'

  • seminar, organized by BIG-N2N
  • where? J. Schell seminar room, UGent-VIB Research building FSVM, Technologiepark 927, 9052 Zwijnaarde (Gent)
  • when? Tuesday March 7, 11:00 - 12:00

Jean-Philippe Vert is professor at the Department of Mathematics at Ecole normale supérieure of Paris, France, director of the Centre for Computational Biology (CBIO) at MINES ParisTech, and team leader at Institut Curie, Paris, France. He graduated from Ecole Polytechnique and has a PhD in mathematics from Paris 6 University. His main research interest is in machine learning and its application to biology, particularly cancer research.

The development of DNA sequencing technologies allows us to collect large amounts of molecular data about the genome of each individual, and opens the possibility to predict drug response or evaluate the risk of various diseases from one's molecular identity. It also raises statistical and computational challenges, as the quantity of data collected per sample is usually far larger than the number of samples available to estimate predictive models. In this talk I will discuss some of these challenges and describe a few methods to attack them through regularization or change of representation, illustrated on applications in cancer prognosis and drug response prediction from gene expression and somatic mutations.