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Nature Inspired Algorithms for Solving Multiple Sequence Alignment Problem: A Review
https://orcid.org/0000-0002-8026-4246
Abstract Multiple Sequence Alignment (MSA) problem is considered an NP-hard problem due to its nature of alignment of more than three or more biological sequences like protein or nucleic acid. Many sequence alignment tools are used to identify regions of similarity that may indicate functional, structural, and/or evolutionary relationships between sequences. Many evolutionary computation techniques have successfully been applied for solving MSA problem. This article presented a state of art review about nature-inspired algorithms, furthermore implemented a few algorithms such as GA, PSO, GSA, BBO, and CRO which are used to solve MSA problem, and in addition to presenting their experimental results along with analysis.
Nature Inspired Algorithms for Solving Multiple Sequence Alignment Problem: A Review
https://orcid.org/0000-0002-8026-4246
Abstract Multiple Sequence Alignment (MSA) problem is considered an NP-hard problem due to its nature of alignment of more than three or more biological sequences like protein or nucleic acid. Many sequence alignment tools are used to identify regions of similarity that may indicate functional, structural, and/or evolutionary relationships between sequences. Many evolutionary computation techniques have successfully been applied for solving MSA problem. This article presented a state of art review about nature-inspired algorithms, furthermore implemented a few algorithms such as GA, PSO, GSA, BBO, and CRO which are used to solve MSA problem, and in addition to presenting their experimental results along with analysis.
Nature Inspired Algorithms for Solving Multiple Sequence Alignment Problem: A Review
https://orcid.org/0000-0002-8026-4246
Abstract Multiple Sequence Alignment (MSA) problem is considered an NP-hard problem due to its nature of alignment of more than three or more biological sequences like protein or nucleic acid. Many sequence alignment tools are used to identify regions of similarity that may indicate functional, structural, and/or evolutionary relationships between sequences. Many evolutionary computation techniques have successfully been applied for solving MSA problem. This article presented a state of art review about nature-inspired algorithms, furthermore implemented a few algorithms such as GA, PSO, GSA, BBO, and CRO which are used to solve MSA problem, and in addition to presenting their experimental results along with analysis.
Nature Inspired Algorithms for Solving Multiple Sequence Alignment Problem: A Review
Paruchuri, Tirumala (author) / Kancharla, Gangadhara Rao (author) / Dara, Suresh (author) / Yadav, Rohit Kumar (author) / Jadav, Surender Singh (author) / Dhamercherla, Swetha (author) / Vidyarthi, Ankit (author)
2022
Article (Journal)
Electronic Resource
English
Nature Inspired Algorithms for Solving Multiple Sequence Alignment Problem: A Review
| Springer Verlag | 2022
Correction to: Nature Inspired Algorithms for Solving Multiple Sequence Alignment Problem: A Review
| Online Contents | 2022
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