DNA motif detection using particle swarm optimization and expectation-maximization

Motif discovery, the process of discovering a meaningful pattern of nucleotides or amino acids that is shared by two or more molecules, is an important part of the study of gene function. In this paper, we propose a hybrid motif discovery approach based upon a combination of particle swarm optimization (PSO) and the expectation-maximization (EM) algorithm. In the proposed algorithm, we use PSO to generate a seed for the EM algorithm.