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An Improved Chemical Reaction-Based Approach for Multiple Sequence Alignment


Affiliations
1 Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India
 

In bioinformatics, multiple sequence alignment (MSA) is an NP-hard problem. Nature-inspired approaches can provide an approximate solution compared to conventional approaches. In this article, the MSA problem is dealt with using chemical reaction optimization (CRO). The limitations of CRO are slow convergence and low population diversity. Therefore, the initialization process is improved by pairwise alignment technique which maintains diversity. In the performance analysis, we have taken benchmark datasets from Bali base version 2.0. The Bali score of the proposed approach is compared with those of the existing approaches such as SB-PIMA, SAGA, RBT-GA and GAPAM, HMMT. Simulation results confirm the superiority of the proposed approach over others.

Keywords

Bioinformatics, Chemical Reaction Optimization, Multiple Sequence Alignment, Population Diversity.
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  • An Improved Chemical Reaction-Based Approach for Multiple Sequence Alignment

Abstract Views: 267  |  PDF Views: 99

Authors

Rohit Kumar Yadav
Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India
Haider Banka
Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India

Abstract


In bioinformatics, multiple sequence alignment (MSA) is an NP-hard problem. Nature-inspired approaches can provide an approximate solution compared to conventional approaches. In this article, the MSA problem is dealt with using chemical reaction optimization (CRO). The limitations of CRO are slow convergence and low population diversity. Therefore, the initialization process is improved by pairwise alignment technique which maintains diversity. In the performance analysis, we have taken benchmark datasets from Bali base version 2.0. The Bali score of the proposed approach is compared with those of the existing approaches such as SB-PIMA, SAGA, RBT-GA and GAPAM, HMMT. Simulation results confirm the superiority of the proposed approach over others.

Keywords


Bioinformatics, Chemical Reaction Optimization, Multiple Sequence Alignment, Population Diversity.



DOI: https://doi.org/10.18520/cs%2Fv112%2Fi03%2F527-538