Laboratoire d'informatique de l'École polytechnique

Bioinfo LIX/LRI joint seminar: Talks by Cédric Chauve and Nelle Varoquaux

Speaker: Cédric Chauve and Nelle Varoquaux
Location: Salle Flajolet, LIX
Date: Thu, 22 Nov 2018, 14:00-16:30

We are pleased to welcome Cédric Chauve (Simon Fraser university) and Nelle Varoquaux (UC Berkeley) next Thursday 22/11, 14h00, at LIX (building Alan Turing, 1 Rue Honoré d'Estienne d'Orves, 91120 Palaiseau) room Philippe Flajolet.

14h00 - Cédric Chauve (Simon Fraser university)

Title: On the Median and Small Parsimony problems in some genome rearrangement models.

Abstract: The main goal of genome rearrangement problems is to compute evolutionary scenarios that can explain the order of genes observed in extant genomes. This naturally leads to questions about the order of genes in ancestral genomes, often of extinct species. If a species phylogeny is given, this problem is known as the Small Parsimony Problem, and in its simplest form, where a single ancestral genome is considered, the Median Problem. Over the last 25+ years, there has been an extremely active research community focusing on these problems. In this talk, I will first review briefly some important results in the field, from initial intractability results to surprising tractability results, and then present some more recent results on (1) how to count or sample optimal solutions to these problems, and (2) how to handle gene duplication. The talk will be relatively free of technical details and will focus on algorithmic questions, leaving aside applications to the described algorithms.

15h10 - Nelle Varoquaux (UC Berkeley)

Tiltle: Studying the three-dimensional structure of DNA from Hi-C data

Abstract: Recent technological advances allow the measurement, in a single Hi-C experiment, of the frequencies of physical contacts among pairs of genomic loci at a genome-wide scale. The next challenge is to infer, from the resulting DNA-DNA contact maps, accurate three dimensional models of how chromosomes fold and fit into the nucleus. I will present a statistical method we developed for inferring genome-wide three-dimensional structure from Hi-C data, based on well-grounded statistical modeling of count data. I will then discuss how these models helped us better understand the links between gene expression and 3D structure of the malaria parasite P. falciparum. Last, I will briefly present how Hi-C data, initially developed to probe the 3D architecture of chromosome can help us annotate the genome. Specifically, I will show how we can identify precisely centromere positions in yeasts using Hi-C count maps.