Journal Article

Localized motif discovery in gene regulatory sequences

Vipin Narang, Ankush Mittal and Wing-Kin Sung

in Bioinformatics

Volume 26, issue 9, pages 1152-1159
Published in print May 2010 | ISSN: 1367-4803
Published online March 2010 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btq106
Localized motif discovery in gene regulatory sequences

More Like This

Show all results sharing this subject:

  • Bioinformatics and Computational Biology

GO

Show Summary Details

Preview

Motivation: Discovery of nucleotide motifs that are localized with respect to a certain biological landmark is important in several appli-cations, such as in regulatory sequences flanking the transcription start site, in the neighborhood of known transcription factor binding sites, and in transcription factor binding regions discovered by massively parallel sequencing (ChIP-Seq).

Results: We report an algorithm called LocalMotif to discover such localized motifs. The algorithm is based on a novel scoring function, called spatial confinement score, which can determine the exact interval of localization of a motif. This score is combined with other existing scoring measures including over-representation and relative entropy to determine the overall prominence of the motif. The approach successfully discovers biologically relevant motifs and their intervals of localization in scenarios where the motifs cannot be discovered by general motif finding tools. It is especially useful for discovering multiple co-localized motifs in a set of regulatory sequences, such as those identified by ChIP-Seq.

Availability and Implementation: The LocalMotif software is available at http://www.comp.nus.edu.sg/~bioinfo/LocalMotif

Contact: ksung@comp.nus.edu.sg

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  6703 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.