DocumentCode
478744
Title
Combining Comparative Genomics with de novo Motif Discovery to Identify Human Transcription Factor DNA-Binding Motifs
Author
Mao, Linyong ; Zheng, W. Jim
Author_Institution
Dept. of Biostat., Med. Univ. of South Carolina, Charleston, SC
Volume
1
fYear
2006
fDate
20-24 June 2006
Firstpage
158
Lastpage
163
Abstract
As more and more genomes are sequenced, comparative genomics approaches provide a methodology for identifying conserved regulatory elements that may be involved in gene regulation. In this study, we combined comparative genomics with de novo motif discovery to identify potential human transcription factor binding motifs that are overrepresented and conserved in the upstream regions of a set of co-regulated genes. We validated our approach by analyzing a well-characterized muscle specific gene set. Our approach also performed better than other existing programs, such as Toucan and Compare Prospector, based on the motif discovery results for the muscle data set
Keywords
DNA; biology computing; data mining; genetics; muscle; de novo motif discovery algorithm; gene regulation; genomics; human transcription factor DNA-binding motifs; muscle data set; muscle specific gene set; Bioinformatics; Cancer; DNA; Genomics; Heuristic algorithms; Humans; Mice; Muscles; Sampling methods; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on
Conference_Location
Hanzhou, Zhejiang
Print_ISBN
0-7695-2581-4
Type
conf
DOI
10.1109/IMSCCS.2006.47
Filename
4673540
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