Skip Navigation



Bioinformatics Advance Access published online on August 27, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth471
Bioinformatics © Oxford University Press 2004; all rights reserved
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
21/1/31    most recent
bth471v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Sumazin, P.
Right arrow Articles by Zhang, M. Q.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sumazin, P.
Right arrow Articles by Zhang, M. Q.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Received September 11, 2003
Revised July 26, 2004
Accepted August 7, 2004

Article

DWE: discriminating word enumerator

Pavel Sumazin 1*, Gengxin Chen 2, Naoya Hata 2, Andrew D. Smith 2, Theresa Zhang 3, Michael Q. Zhang 2

1 Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA; Computer Science Department, Portland State University, P.O. Box 751, Portland, OR 97207, USA
2 Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA
3 Bioinformatics, Merck Research Laboratories, Rahway, NJ 07065, USA

* To whom correspondence should be addressed. E-mail: ps{at}cs.pdx.edu.


  Abstract

Motivation: Tissue-specific transcription-factor binding sites give insight into tissue-specific transcription regulation.

Results: We describe a word-counting-based tool for de novo tissue-specific transcription-factor binding site discovery using expression information in addition to sequence information. We incorporate tissue-specific gene expression through gene classification to positive expression and repressed expression. We present a direct statistical approach to find over-represented transcription-factor binding sites in a foreground promoter sequence set against a background promoter sequence set. Our approach naturally extends to synergistic transcription factor binding site search.

We find putative transcription factor binding sites that are over represented in the proximal promoters of liver-specific genes relative to proximal promoters of liver-independent genes. Our results indicate that binding sites for hepatocyte nuclear factors (especially HNF-1 and HNF-4) and CCAAT/enhancer-binding protein (C/EBP{beta}) are the most over represented in proximal promoters of liver-specific genes. Our results suggest that HNF-4 has strong synergistic relationships with hepatocyte nuclear factors HNF-1, HNF-4 and HNF-3{beta} and with C/EBP{beta}.

Availability: Programs are available for use over the web at http://rulai.cshl.edu/tools/dwe.

Supplementary Information: Data and omitted results are available at http://rulai.cshl.edu/tools/dwe/supp.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Brief BioinformHome page
A. Yu. Mitrophanov and M. Borodovsky
Statistical significance in biological sequence analysis
Brief Bioinform, March 1, 2006; 7(1): 2 - 24.



Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.