Hybridizing biogeography-based optimization with differential evolution for motif discovery problem

作者：Feng S L; Zhu Q X; Gong X J^*; Zhong S

来源：ICIC Express Letters, 2013, 7(12): 3343-3348.

• Biogeography-based optimization
• Differential evolution
• Motif discovery

The computational discovery of DNA motifs for previously uncharacterized transcription factors in groups of co-regulated genes is a well-studied problem with a great deal of practical relevance to the biologist. In this paper, we apply an improved hybridization of Biogeography-Based Optimization (BBO) with differential evolution (DE) approach, namely BBO/DE, to predict motifs from DNA sequences. BBO/DE combines the exploitation of BBO with the exploration of DE effectively, and hence it can generate the promising candidate solutions. And the migration operators of BBO are modified based on number of iteration to meet motif discovery requirements. Statistical comparisons with some typical existing approaches on three commonly used datasets are provided, which demonstrates the validity and effectiveness of the proposed improved hybrid algorithm.

• 出版日期2013
• 单位天津大学; 电子科技大学