A steganalysis-based approach to comprehensive identification and characterization of functional regulatory elements.
The comprehensive identification of cis-regulatory elements on a genome scale is a challenging problem. We develop a novel, steganalysis-based approach for genome-wide motif finding, called WordSpy, by viewing regulatory regions as a stegoscript with cis-elements embedded in 'background' sequences. We apply WordSpy to the promoters of cell-cycle-related genes of Saccharomyces cerevisiae and Arabidopsis thaliana, identifying all known cell-cycle motifs with high ranking. WordSpy can discover a complete set of cis-elements and facilitate the systematic study of regulatory networks.
Wang
Guandong
G
Department of Computer Science and Engineering, Washington University, St, Louis, MO 63130, USA.
Zhang
Weixiong
W
D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics; D001483:Base Sequence; D002453:Cell Cycle; D005786:Gene Expression Regulation; D023281:Genomics / Q000379:methods*; D008390:Markov Chains; D008954:Models, Biological; D008969:Molecular Sequence Data; D050436:Regulatory Elements, Transcriptional; D012441:Saccharomyces cerevisiae / Q000235:genetics