title: [Inference of transcriptional regulatory networks].
abstract: The cell is a very complex system and although molecular biology allowed spectacular progresses, biologists are currently trying to tackle complexity at the system level, to unravel cell mysteries. The inference of transcriptional regulatory networks, the characterization of their topology, their dynamic, their role in major cell functions is at the heart of this strategy. We are proposing a systemic approach, based on integration of large scale data such as expression profiling, ChIP on chip analysis and high throughput RNA interference using siRNA microarrays to infer these networks and characterize associated phenotypes. Ultimately, the characterization of the properties of these networks should impact our understanding of biology and offer potential applications in medicine and pharmacology.
authors.affiliation: CEA, DSV, IRCM, Laboratoire d'Exploration Fonctionnelle des Génomes, Evry, France. xavier.gidrol@cea.fr
authors.forename: Xavier
authors.initials: X
authors.lastname: Gidrol
authors.forename: Ning
authors.initials: N
authors.lastname: Wu
authors.forename: Vincent
authors.initials: V
authors.lastname: Frouin
authors.forename: Marie-Anne
authors.initials: MA
authors.lastname: Debily
mesh_terms: D000818:Animals; D002843:Chromatin / Q000235:genetics; D006706:Homeostasis; D008322:Mammals; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D010957:Plasmids; D014158:Transcription, Genetic
chemical_list: D002843:Chromatin