Position-dependent motif characterization using non-negative matrix factorization.

ABSTRACT:

Motivation

Cis-acting regulatory elements are frequently constrained by both sequence content and positioning relative to a functional site, such as a splice or polyadenylation site. We describe an approach to regulatory motif analysis based on non-negative matrix factorization (NMF). Whereas existing pattern recognition algorithms commonly focus primarily on sequence content, our method simultaneously characterizes both positioning and sequence content of putative motifs.

Results

Tests on artificially generated sequences show that NMF can faithfully reproduce both positioning and content of test motifs. We show how the variation of the residual sum of squares can be used to give a robust estimate of the number of motifs or patterns in a sequence set. Our analysis distinguis

SUBMITTER: Hutchins LN 

PROVIDER: S-EPMC2639279 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature