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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.
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