MOPAT: a graph-based method to predict recurrent cis-regulatory modules from known motifs.

ABSTRACT: The identification of cis-regulatory modules (CRMs) can greatly advance our understanding of eukaryotic regulatory mechanism. Current methods to predict CRMs from known motifs either depend on multiple alignments or can only deal with a small number of known motifs provided by users. These methods are problematic when binding sites are not well aligned in multiple alignments or when the number of input known motifs is large. We thus developed a new CRM identification method MOPAT (motif pair tree), which identifies CRMs through the identification of motif modules, groups of motifs co-occurring in multiple CRMs. It can identify 'orthologous' CRMs without multiple alignments. It can also find CRMs given a large number of known motifs. We have applied this method to mouse developmental genes,

SUBMITTER: Hu J 

PROVIDER: S-EPMC2490743 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature