Camille Charbonnier

Inférence de réseaux de régulation génétique à partir de données du transcriptome non indépendamment et indentiquement distribuées (2009-2012)

Camille’s PhD was co-supervised with Christophe Ambroise (50%/50%), from 2009 to 2012.

Summary

This thesis develops statistical methods for inferring gene regulatory networks from transcriptomic data that violate the classical independent and identically distributed (iid) sampling assumption, in particular time-course and structured experimental designs. It proposes weighted-Lasso and cooperative-Lasso penalized estimators of Gaussian graphical models that incorporate prior structural information (temporal ordering, replicate structure) to improve network recovery, together with model selection procedures adapted to these dependent settings. The resulting methods are implemented in the SIMoNe R package and applied to real transcriptomic time-course data.

PhD manucript

2012

  1. PhD thesis
    Inférence de réseaux de régulation génétique à partir de données du transcriptome non indépendamment et identiquement distribuées
    Camille Charbonnier
    Université d’Évry-Val-d’Essonne, 2012

Journal papers

2012

  1. Ann Appl Stat
    Sparsity in sign-coherent groups of variables via the cooperative-Lasso
    Julien Chiquet, Y. Grandvalet, and C. Charbonnier
    The Annals of Applied Statistics, 2012

2010

  1. SAGMB
    Weighted-Lasso for structured network inference from time course data
    C. Charbonnier, Julien Chiquet, and C. Ambroise
    Statistical Applications in Genomics and Molecular Biology, 2010

2014

  1. Probabilistic graphical models dedicated to applications in genetics, genomics and postgenomics
    M. Jeanmougin, C. Charbonnier, M. Guedj, and 1 more author
    2014

Conferences

2011

  1. Sparsity with sign-coherent groups of variables via the cooperative-Lasso
    J. Chiquet, Y. Grandvalet, and C. Charbonnier
    In Proceedings of SPARS’11, Edinburgh, 2011

2010

  1. Gene expression signature in whole blood after treatment with amino acid copolymer PI-2301 in multiple sclerosis
    JC Corvol, C Vrignaud, K Tahiri, and 11 more authors
    In European Committee for Treatment and Research in Multiple Sclerosis, 2010

2010

  1. Weighted-Lasso for Structured Network Inference for Time-Course data
    C. Charbonnier, J. Chiquet, and C. Ambroise
    In JOBIM’10, Montpellier, 2010

2009

  1. SIMoNe : Statistical Inference for Modular Networks
    J. Chiquet, C. Charbonnier, and C. Ambroise
    In Workshop MODGRAPH, JOBIM’09, Nantes, 2009