Parallelizing a Hybrid Multiobjective Differential Evolution for Identifying Cis-Regulatory Elements

A cis-regulatory element is a non-coding DNA sequence in or near a gene required for its expression, often containing transcription factors binding sites (TFBS). Identifying new TFBSs is fundamental to understand the regulation process of these genes. The optimization problem responsible for these findings is the Motif Discovery Problem (MDP), which is formulated as a short DNA pattern discovery problem. In addition, the MDP is an NP-hard optimization problem since it has to find short strings mixed among a large amount of biological information. In this paper, we propose and study a new hybrid multiobjective evolutionary algorithm based on Differential Evolution (DE) named Hybrid Differential Evolution with Pareto Tournaments (H-DEPT). To demonstrate the superiority of our proposed algorithm on a biological level, we compare the predictions made with those predicted by MEME, BioProspector and BioOptimizer when solving a set of four real sequence datasets. Finally, by using OpenMP, we also demonstrate that this algorithm is highly suitable to be parallelized. As we will see, we have performed several experiments with multi-core systems of 2, 4, and 8 cores; obtaining good parallel results.