IBBOMSA: An Improved Biogeography-based Approach for Multiple Sequence Alignment. (January 2016)

• Record Type: Journal Article
• Authors: Yadav, Rohit Kumar; Banka, Haider
• Is Part Of: Evolutionary bioinformatics online. Volume 12(2016)
• Publication Date: 2016-01
• Subjects: Multiple sequence alignment (MSA) -- biogeography-based optimization (BBO) -- migration operator -- diversity; Bioinformatics -- Periodicals; Evolutionary computation -- Periodicals; Genetic programming (Computer science) -- Periodicals; Computational Biology; Evolution, Molecular; Bioinformatics; Electronic journals; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 576.8
• DOI: 10.4137/EBO.S40457
• Languages: English
• ISSNs: 1176-9343

Abstract

In bioinformatics, multiple sequence alignment (MSA) is an NP-hard problem. Hence, nature-inspired techniques can better approximate the solution. In the current study, a novel biogeography-based optimization (NBBO) is proposed to solve an MSA problem. The biogeography-based optimization (BBO) is a new paradigm for optimization. But, there exists some deficiencies in solving complicated problems such as low population diversity and slow convergence rate. NBBO is an enhanced version of BBO, in which, a new migration operation is proposed to overcome the limitations of BBO. The new migration adopts more information from other habitats, maintains population diversity, and preserves exploitation ability. In the performance analysis, the proposed and existing techniques such as VDGA, MOMSA, and GAPAM are tested on publicly available benchmark datasets (ie, Bali base). It has been observed that the proposed method shows the superiority/competitiveness with the existing techniques.