Identification of functional modules based on transcriptional regulation structure

Etienne Birmele (1) , Mohamed Elati (2) , Céline Rouveirol (3) , Christophe Ambroise (1)

1 SG - Laboratoire Statistique et Génome
2 Programme d'Épigénomique
3 LIPN - Laboratoire d'Informatique de Paris-Nord

BACKGROUND: Identifying gene functional modules is an important step towards elucidating gene functions at a global scale. Clustering algorithms mostly rely on co-expression of genes, that is group together genes having similar expression profiles. RESULTS: We propose to cluster genes by co-regulation rather than by co-expression. We therefore present an inference algorithm for detecting co-regulated groups from gene expression data and introduce a method to cluster genes given that inferred regulatory structure. Finally, we propose to validate the clustering through a score based on the GO enrichment of the obtained groups of genes. CONCLUSION: We evaluate the methods on the stress response of S. Cerevisiae data and obtain better scores than clustering obtained directly from gene expression.

Domaines: Statistiques [math.ST]; Théorie [stat.TH]; Bio-Informatique, Biologie Systémique [q-bio.QM]; Bio-informatique [q-bio.QM]

Etienne Birmele, Mohamed Elati, Céline Rouveirol, Christophe Ambroise. Identification of functional modules based on transcriptional regulation structure. BMC Proceedings, 2008, 2 (4), pp.S4. ⟨hal-00730904⟩