An evolutionary Monte Carlo algorithm for identifying short adjacent repeats in multiple sequences

Evolutionary Monte Carlo (EMC) algorithm is an effective and powerful method to sample complicated distributions. Short adjacent repeats identification problem (SARIP), i.e., searching for the common sequence pattern in multiple DNA sequences, is considered as one of the key challenges in the field of bioinformatics. A recently proposed Markov chain Monte Carlo (MCMC) algorithm has demonstrated its effectiveness in solving SARIP. However, high computation time and inevitable local optima hinder its wide application. In this paper, we apply EMC to parallelize the MCMC algorithm to solve SARIP. Our proposed EMC scheme is implemented on a parallel platform and the simulation results show that, compared with the conventional MCMC algorithm, EMC not only improves the quality of final solution but also reduces the computation time. ©2010 IEEE.published_or_final_versionThe 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Hong Kong, China, 18-21 December 2010. In Proceedings of BIBM, 2010, p. 643-64