Skip to main content
Article thumbnail
Location of Repository

Regulatory motif discovery using a population clustering evolutionary algorithm

By Michael A. Lones and Andy M. Tyrrell

Abstract

This paper describes a novel evolutionary algorithm for regulatory motif discovery in DNA promoter sequences. The algorithm uses data clustering to logically distribute the evolving population across the search space. Mating then takes place within local regions of the population, promoting overall solution diversity and encouraging discovery of multiple solutions. Experiments using synthetic data sets have demonstrated the algorithm's capacity to find position frequency matrix models of known regulatory motifs in relatively long promoter sequences. These experiments have also shown the algorithm's ability to maintain diversity during search and discover multiple motifs within a single population. The utility of the algorithm for discovering motifs in real biological data is demonstrated by its ability to find meaningful motifs within muscle-specific regulatory sequences

Year: 2007
DOI identifier: 10.1109/tcbb.2007.1044
OAI identifier: oai:eprints.whiterose.ac.uk:3419

Suggested articles


To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.