title: A model for gene deregulation detection using expression data.
abstract: In tumoral cells, gene regulation mechanisms are severely altered. Genes that do not react normally to their regulators' activity can provide explanations for the tumoral behavior, and be characteristic of cancer subtypes. We thus propose a statistical methodology to identify the misregulated genes given a reference network and gene expression data.
authors.forename: Thomas
authors.initials: T
authors.lastname: Picchetti
authors.forename: Julien
authors.initials: J
authors.lastname: Chiquet
authors.forename: Mohamed
authors.initials: M
authors.lastname: Elati
authors.forename: Pierre
authors.initials: P
authors.lastname: Neuvial
authors.forename: Rémy
authors.initials: R
authors.lastname: Nicolle
authors.forename: Etienne
authors.initials: E
authors.lastname: Birmelé
mesh_terms: D000465:Algorithms; D005189:False Positive Reactions; D053263:Gene Regulatory Networks; D006801:Humans; D008957:Models, Genetic; D059467:Transcriptome; D001749:Urinary Bladder Neoplasms / Q000235:genetics