Multiple Sequence Alignment using Modified Brain Storm Optimization Algorithm with new Mutant

Multiple Sequence Alignment using Modified Brain Storm Optimization Algorithm with new Mutant
  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-2
Year of Publication : 2022
Authors : Jeevana Jyothi Pujari, Kanadam Karteeka Pavan
DOI :  10.14445/22315381/IJETT-V70I2P206

How to Cite?

Jeevana Jyothi Pujari, Kanadam Karteeka Pavan, "Multiple Sequence Alignment using Modified Brain Storm Optimization Algorithm with new Mutant," International Journal of Engineering Trends and Technology, vol. 70, no. 3, pp. 48-53, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I2P206

Abstract
Multiple Sequence Alignment (MSA) is a challenging and computational task in bioinformatics and is a core and fundamental task for various biological analysis fields. Finding an optimized alignment is a very difficult task in sequence alignment problems. One of the new intelligence algorithms is the Brainstorm optimization Algorithm(BSO), which solves many optimization problems due to its unique capabilities. BSO can be trapped into local optima with successive iterations. To address this local optimum, we proposed a Modified Brain storm optimization algorithm with a new mutation operator (MBSO-Mu) to obtain more optimal alignments. This modified new mutant mechanism is incorporated into creating new ideas in BSO for enhancing search space capability by maintaining population diversity. The proposed Algorithm has been executed on various benchmark datasets to obtain the fitness score of alignments. The efficacy of the proposed with a mutant MBSO-Mu shows a more optimal and near-optimal alignment score in multiple sequences while compared to several evolutionary algorithms.

Keywords
MSA, MBSO-MU, BSO, Encoding candidate.

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