Skip Navigation


Bioinformatics Advance Access originally published online on February 18, 2007
Bioinformatics 2007 23(8):933-941; doi:10.1093/bioinformatics/btm055
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrowOA All Versions of this Article:
23/8/933    most recent
btm055v1
Right arrow Alert me when this article is cited
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 arrow Search for citing articles in:
ISI Web of Science (3)
Google Scholar
Right arrow Articles by Tomovic, A.
Right arrow Articles by Oakeley, E. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Tomovic, A.
Right arrow Articles by Oakeley, E. J.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Position dependencies in transcription factor binding sites

Andrija Tomovic and Edward J. Oakeley *

Friedrich Miescher Institute for Biomedical Research, Novartis Research Foundation, Maulbeerstrasse 66, CH-4058 Basel, Switzerland

*To whom correspondence should be addressed.


  Abstract

Motivation: Most of the available tools for transcription factor binding site prediction are based on methods which assume no sequence dependence between the binding site base positions. Our primary objective was to investigate the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and to use the resulting data to develop improved scoring functions for binding-site prediction.

Results: Using three statistical tests, we analyzed the number of binding sites showing dependent positions. We analyzed transcription factor–DNA crystal structures for evidence of position dependence. Our final conclusions were that some factors show evidence of dependencies whereas others do not. We observed that the conformational energy (Z-score) of the transcription factor–DNA complexes was lower (better) for sequences that showed dependency than for those that did not (P < 0.02). We suggest that where evidence exists for dependencies, these should be modeled to improve binding-site predictions. However, when no significant dependency is found, this correction should be omitted. This may be done by converting any existing scoring function which assumes independence into a form which includes a dependency correction. We present an example of such an algorithm and its implementation as a web tool.

Availability: http://promoterplot.fmi.ch/cgi-bin/dep.html

Contact: edward.oakeley{at}fmi.ch

Supplementary information: Supplementary data (1, 2, 3, 4, 5, 6, 7 and 8) are available at Bioinformatics online.

Associate Editor: Alfonso Valencia

Received on October 29, 2006; revised on January 17, 2007; accepted on February 9, 2007

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
 Nucleic Acids ResHome page
B. Hooghe, P. Hulpiau, F. van Roy, and P. De Bleser
ConTra: a promoter alignment analysis tool for identification of transcription factor binding sites across species
Nucleic Acids Res., July 1, 2008; 36(suppl_2): W128 - W132.
[Abstract] [Full Text] [PDF]

Home page
 DNA ResHome page
A. Vandenbon, Y. Miyamoto, N. Takimoto, T. Kusakabe, and K. Nakai
Markov Chain-based Promoter Structure Modeling for Tissue-specific Expression Pattern Prediction
DNA Res, February 7, 2008; (2008) dsm034v1.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
L. Segal, M. Lapidot, Z. Solan, E. Ruppin, Y. Pilpel, and D. Horn
Nucleotide variation of regulatory motifs may lead to distinct expression patterns
Bioinformatics, July 1, 2007; 23(13): i440 - i449.
[Abstract] [Full Text] [PDF]


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.