A particle swarm optimization-based algorithm for finding gapped motifs.

ABSTRACT:

Background

Identifying approximately repeated patterns, or motifs, in DNA sequences from a set of co-regulated genes is an important step towards deciphering the complex gene regulatory networks and understanding gene functions.

Results

In this work, we develop a novel motif finding algorithm (PSO+) using a population-based stochastic optimization technique called Particle Swarm Optimization (PSO), which has been shown to be effective in optimizing difficult multidimensional problems in continuous domains. We propose a modification of the standard PSO algorithm to handle discrete values, such as characters in DNA sequences. The algorithm provides several features. First, we use both consensus and position-specific weight matrix representations in our algorithm, taking advant

SUBMITTER: Lei C 

PROVIDER: S-EPMC3022572 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature