title: Identification of mouse heart transcriptomic network sensitive to various heart diseases.
abstract: Exploring biological systems from highly complex datasets is an important task for systems biology. The present study examined co-expression dynamics of mouse heart transcriptome by spectral graph clustering (SGC) to identify a heart transcriptomic network. SGC of microarray data produced 17 classified biological conditions (called condition spectrum, CS) and co-expression patterns by generating bi-clusters. The results showed dynamic co-expression patterns with a modular structure enriched in heart-related CS (CS-1 and -13) containing abundant heart-related microarray data. Consequently, a mouse heart transcriptomic network was constructed by clique analysis from the gene clusters exclusively present in the heart-related CS; 31 cliques were used for constructing the network. The participating genes in the network were closely associated with important cardiac functions (e. g., development, lipid and glycogen metabolisms). Online Mendelian Inheritance in Man (OMIM) database indicates that mutations of the genes in the network induced serious heart diseases. Many of the tested genes in the network showed significantly altered gene expression in an animal model of hypertrophy. The results suggest that the present approach is critical for constructing a heart-related transcriptomic network and for deducing important genes involved in the pathogenesis of various heart diseases.
authors.affiliation: Department of Life Science, Gwangju Institute of Science and Technology, Gwangju, Korea.
authors.forename: Seong-Eui
authors.initials: SE
authors.lastname: Hong
authors.forename: Inju
authors.initials: I
authors.lastname: Park
authors.forename: Hyeseon
authors.initials: H
authors.lastname: Cha
authors.forename: Seong-Hwan
authors.initials: SH
authors.lastname: Rho
authors.forename: Woo Jin
authors.initials: WJ
authors.lastname: Park
authors.forename: Chunghee
authors.initials: C
authors.lastname: Cho
authors.forename: Do Han
authors.initials: DH
authors.lastname: Kim
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006331:Heart Diseases / Q000378:metabolism*; D051379:Mice; D008955:Models, Cardiovascular; D005810:Multigene Family; D009206:Myocardium / Q000378:metabolism*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D020543:Proteome; D014157:Transcription Factors