U Keich1, P A Pevzner. 1. Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093, USA. keich@cs.ucsd.edu
Abstract
MOTIVATION: Gene activity is often affected by binding transcription factors to short fragments in DNA sequences called motifs. Identification of subtle regulatory motifs in a DNA sequence is a difficult pattern recognition problem. In this paper we design a new motif finding algorithm that can detect very subtle motifs. RESULTS: We introduce the notion of a multiprofile and use it for finding subtle motifs in DNA sequences. Multiprofiles generalize the notion of a profile and allow one to detect subtle patterns that escape detection by the standard profiles. Our MULTIPROFILER algorithm outperforms other leading motif finding algorithms in a number of synthetic models. Moreover, it can be shown that in some previously studied motif models, MULTIPROFILER is capable of pushing the performance envelope to its theoretical limits. AVAILABILITY: http://www-cse.ucsd.edu/groups/bioinformatics/software.html
MOTIVATION: Gene activity is often affected by binding transcription factors to short fragments in DNA sequences called motifs. Identification of subtle regulatory motifs in a DNA sequence is a difficult pattern recognition problem. In this paper we design a new motif finding algorithm that can detect very subtle motifs. RESULTS: We introduce the notion of a multiprofile and use it for finding subtle motifs in DNA sequences. Multiprofiles generalize the notion of a profile and allow one to detect subtle patterns that escape detection by the standard profiles. Our MULTIPROFILER algorithm outperforms other leading motif finding algorithms in a number of synthetic models. Moreover, it can be shown that in some previously studied motif models, MULTIPROFILER is capable of pushing the performance envelope to its theoretical limits. AVAILABILITY: http://www-cse.ucsd.edu/groups/bioinformatics/software.html