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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Published in | The Journal of supercomputing Vol. 79; no. 2; pp. 1201 - 1234 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
01.02.2023
Springer Nature B.V |
Subjects | |
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 |