An Iterative Algorithm for Motif Discovery

Analysis of DNA Sequence motifs is becoming increasingly important in the study of gene regulation, and the identification of motif in DNA sequences is a very complex problem in computational biology. In this paper, we propose a method that employs the general GA framework and computes the motifs from the shot motif length to the standard length with three operation in GA and a new operation called Addition proposed by us. The experiment results on simulated data and real biological data show that the obtained motifs are consistent with the real ones. Moreover, our method gets higher score than the other three methods: Gibbs Sampler, Genetic Algorithm (GA) and GARPS algorithm in terms of the data CRP. In addition, our algorithm is a parallel random search that is beneficial to implement parallel computing to increase computational efficiency of the algorithm.