Discriminative motif discovery in DNA and protein sequences using the DEME algorithm

Background: Motif discovery aims to detect short, highly conserved patterns in a collection of unaligned DNA or protein sequences. Discriminative motif finding algorithms aim to increase the sensitivity and selectivity of motif discovery by utilizing a second set of sequences, and searching only for patterns that can differentiate the two sets of sequences. Potential applications of discriminative motif discovery include discovering transcription factor binding site motifs in ChIPchip data and finding protein motifs involved in thermal stability using sets of orthologous proteins from thermophilic and mesophilic organisms. Results: We describe DEME, a discriminative motif discovery algorithm for use with protein and DNA sequences. Input to DEME is two sets of sequences; a "positive" set and a "negative" set. DEME represents motifs using a probabilistic model, and uses a novel combination of global and local search to find the motif that optimally discriminates betw...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Emma Redhead, Timothy L. Bailey
• Keywords: BMCBI 2007, Discriminative Motif, Discriminative Motif Discovery, Motif Discovery