Parallel protein multiple sequence alignment approaches: a systematic literature review

Multiple sequence alignment approaches refer to algorithmic solutions for the alignment of biological sequences. Since multiple sequence alignment has exponential time complexity when a dynamic programming approach is applied, a substantial number of parallel computing approaches have been implement...

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Bibliographic Details
Published in:The Journal of supercomputing Vol. 79; no. 2; pp. 1201 - 1234
Main Authors: Almanza-Ruiz, Sergio H., Chavoya, Arturo, Duran-Limon, Hector A.
Format: Journal Article
Language:English
Published: New York Springer US 01.02.2023
Springer Nature B.V
Subjects:
Algorithms
Alignment
Amino acids
Bioinformatics
Compilers
Computer Science
Digital systems
Dynamic programming
Genomics
Interpreters
Keywords
Literature reviews
Processor Architectures
Programming Languages
Proteins
Systematic review
Systematic review
Parallel programming
Multiple sequence alignment
Protein
ISSN:0920-8542, 1573-0484
Online Access:Get full text
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Summary:Multiple sequence alignment approaches refer to algorithmic solutions for the alignment of biological sequences. Since multiple sequence alignment has exponential time complexity when a dynamic programming approach is applied, a substantial number of parallel computing approaches have been implemented in the last two decades to improve their performance. In this paper, we present a systematic literature review of parallel computing approaches applied to multiple sequence alignment algorithms for proteins, published in the open literature from 1988 to 2022; we extracted articles from four scientific databases: ACM Digital Library, IEEE Xplore, Science Direct and SpringerLink, and four journals: Bioinformatics, PLOS Computational Biology, PLOS ONE, and Scientific Reports. Additionally, in order to cover other potential databases and journals, we performed a transversal search through Google Scholar. We conducted a selection process that yielded 106 research articles; then, we analyzed these articles and defined a classification framework. Additionally, we point out some directions and trends for parallel computing approaches for multiple sequence alignment, as well as some unsolved problems.
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-022-04697-9