IBBOMSA:一种基于生物地理学的多序列比对改进方法

R. Yadav, H. Banka
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引用次数: 6

摘要

在生物信息学中,多序列比对(MSA)是一个np难题。因此,受自然启发的技术可以更好地近似解决方案。本研究提出了一种新的基于生物地理的优化方法来解决MSA问题。基于生物地理的优化(BBO)是一种新的优化范式。但在解决种群多样性低、收敛速度慢等复杂问题方面存在不足。NBBO是BBO的增强版,它提出了一种新的迁移操作来克服BBO的局限性。新移民从其他栖息地吸收了更多的信息,保持了种群的多样性,并保留了开发能力。在性能分析中,提出的和现有的VDGA、MOMSA和GAPAM等技术在公开可用的基准数据集(即Bali base)上进行了测试。已经观察到,所提出的方法与现有技术相比具有优势/竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IBBOMSA: An Improved Biogeography-based Approach for Multiple Sequence Alignment
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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