Localized motif discovery in gene regulatory sequences.
BACKGROUND
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.


METHODS
The LocalMotif software is available at http://www.comp.nus.edu.sg/~bioinfo/LocalMotif.
Department of Computer Science, National University of Singapore, Singapore.
Vipin
V
Narang
Ankush
A
Mittal
Wing-Kin
WK
Sung
D000465:Algorithms; D020816:Amino Acid Motifs; D000595:Amino Acid Sequence; D000818:Animals; D047369:Chromatin Immunoprecipitation; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D053263:Gene Regulatory Networks; D006801:Humans; D051379:Mice; D015233:Models, Statistical; D008969:Molecular Sequence Data; D016415:Sequence Alignment / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software