Dissecting the transcription networks of a cell using computational genomics.
A great challenge in understanding biological complexity in the post-genome era is to reconstruct the regulatory networks governing the patterns of gene expression. In the past few years, the rapid accumulation of genomic sequence and functional data has led to the development of computational approaches to systematically dissect transcriptional regulatory networks. Effective algorithms have been developed to predict cis-regulatory elements in a genome, to identify the target genes of transcription factors, to infer the conditions under which each transcription factor is either activated or deactivated, and to analyze combinatorial regulation by multiple transcription factors. Genomic approaches have profoundly changed the way biologists investigate transcriptional regulation, and global pictures of the transcription networks for several model organisms are beginning to emerge.
Li
Hao
H
Department of Biochemistry and Biophysics, University of California at San Francisco, 600 16th Street, San Francisco, CA 94143-2240, USA. haoli@genome.ucsf.edu
Wang
Wei
W
D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods* / Q000639:trends; D005786:Gene Expression Regulation; D023281:Genomics / Q000379:methods* / Q000639:trends; D006801:Humans; D012045:Regulatory Sequences, Nucleic Acid; D014157:Transcription Factors; D014158:Transcription, Genetic
D014157:Transcription Factors