Hybridizing Biogeography-Based Optimization with Differential Evolution for Motif Discovery Problem

摘要：

　　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 applied 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 were 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.

关键词： Biogeography-Based Optimization Differential evolution motif discovery

作者: Si-ling Feng Qing-xin Zhu Xiu-jun Gong Sheng Zhong

作者单位: School of Computer Science&Engineering,University of Electronic Science&Technology of China,Chengdu, School of Computer Science&Engineering,University of Electronic Science&Technology of China,Chengdu, School of Computer Science and Technology,Tianjin University,Tianjin,China College of Information Science & Technology,Hainan University,Haikou,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Science and Social Research (2013年第二届科学与社会研究国际会议)(ICSSR2013)

会议地点: 北京

会议语种:英文

页码: 304-308

在线出版日期: 2013-07-13（万方平台首次上网日期，不代表论文的发表时间）