Statistical Methods for Post Genomic Data 2014, à Paris

Dec 10 2013 - 10:10

Paris, UPMC campus

Short description of the event: 

This workshop aims at gathering statisticians, computer scientists, and biologists to discuss new statistical methodologies for the analysis of high throughput biological data and the challenge arising herein.

Invited Speakers

Protein structure: David T. Jones (Computer Science, University College London)
Evolution: Frédéric Austerlitz (Eco-anthropologie et Ethnologie, Museum National d'Histoire Naturelle)
Big Data: Arnak Dalalyan (ENSAE / CREST, GENES and Imagine / LIGM, Université Paris-Est )
Phylogeny: Cécile Ané (Department of Statistics and Botanics, University of Wisconsin-Madison)

Contributed Sessions

Metabolism (organizer: Daniel Kahn, abstracts)
David Vallenet (Laboratoire de génomique comparative, Génoscope)
Enzyme survey and how to find new ones
Christoph Kaleta (Theoretical Systems Biology Friedrich-Schiller-Universität Jena)
Tuned for speed – Elucidation of strategies for rapid metabolic adaptations in prokaryotes
Frank J. Bruggeman (Systems Bioinformatics, VU University, Amsterdam)
Constraints, adaptability and optimality of metabolic networks

Statistical Genomics (organizer: Bertrand Servin)
Simon Boitard (Origine, Structure et Evolution de la Biodiversité, Museum National d'Histoire Naturelle) :
Inferring the past dynamics of effective population size using genome wide molecular data
Christèle Robert-Granié (INRA) :
Integration of genomic information into genetic evaluation model : Is it a good statistical model?
Anne-Louise Leutenegger (Genetic Variation and Human Diseases Lab, INSERM):
Mapping genes in consanguineous and isolated populations in the era of high throughput sequencing

Phylogeny (organizer: Nicolas Lartillot, abstracts)
Alessandra Carbone (LGM, Université Pierre et Marie Curie - CNRS)
Coding of evolutionary pathways in proteins: from sequence to function
Emmanuel Paradis (Institut de recherche pour le développement - ISEM UMR 226/5554 - UM2/CNRS/IRD)
Phylogenetic tree space and Markov Chain Monte Carlo methods
Gergely J. Szöllősi (ELTE-MTA Biophysics Research Group - Eötvös University)
Efficient Exploration of the Space of Reconciled Gene Trees

Additionally, sessions of contributed communications (15 min) and a poster session will be organized, please consider submit your work !