title: Grid methodology for identifying co-regulated genes and transcription factor binding sites.
abstract: The identification of the genes that are coordinately regulated is an important and challenging task of bioinformatics and represents a first step in the elucidation of the topology of transcriptional networks. We first compare the performances, in a grid setting, of the Markov clustering algorithm with respect to the k-means using microarray test data sets. The gene expression information of the clustered genes can be used to annotate transcription binding sites upstream co-regulated genes. The methodology uses a regression model that relates gene expression levels to the matching scores of nucleotide patterns allowing us to identify DNA-binding sites from a collection of noncoding DNA sequences from co-regulated genes. Here we discuss extending the approach to multiple species exploiting the grid framework.
authors: University of Cambridge Computer Laboratory, Cambridge CB3 OFD, UK. ecv22@cam.ac.uk
authors: Elizabeth
authors: E
authors: van der Wath
authors: Loukas
authors: L
authors: Moutsianas
authors: Richard
authors: R
authors: van der Wath
authors: Alet
authors: A
authors: Visagie
authors: Luciano
authors: L
authors: Milanesi
authors: Pietro
authors: P
authors: Liò
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics*; D016247:Information Storage and Retrieval / Q000379:methods; D020407:Internet; D005810:Multigene Family / Q000235:genetics*; D011485:Protein Binding; D014157:Transcription Factors / Q000235:genetics*
chemical_list: D014157:Transcription Factors