Metaheuristics for multiple sequence alignment: A systematic review

• Published in: Computational biology and chemistry Vol. 94; p. 107563
• Main Authors: Amorim, Anderson Rici, Zafalon, Geraldo Francisco Donegá, Contessoto, Allan de Godoi, Valêncio, Carlos Roberto, Sato, Liria Matsumoto
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2021
• Subjects: Bioinformatics; Metaheuristics; Multi-objective optimization; Multiple sequence alignment; Systematic literature review; Multi-objective optimization; Multiple sequence alignment; Metaheuristics; Bioinformatics; Systematic literature review
• ISSN: 1476-9271; 1476-928X; 1476-928X
• DOI: 10.1016/j.compbiolchem.2021.107563

The Multiple Sequence Alignment (MSA) is a key task in bioinformatics, because it is used in different important biological analysis, such as function and structure prediction of unknown proteins. There are several approaches to perform MSA and the use of metaheuristics stands out because of the search ability of these methods, which generally leads to good results in a reasonable amount of time. This paper presents a Systematic Literature Review (SLR) on metaheuristics for MSA, compiling relevant works published between 2014 and 2019. The results of our SLR show the constant interest in this subject, due to the several recent publications that use different metaheuristics to obtain more accurate alignments. Moreover, the final results of our SLR show a multi-objective and hybrid approaches trends, which generally leads these methods to achieve even better results. Thus, we show in this work how the use of metaheuristics to perform MSA still remains an important and promising open research field. [Display omitted] •A Systematic Literature Review of metaheuristics applied to solve the multiple sequence alignment problem is executed.•The Systematic Literature Review methodology is detailed.•Critical analysis of 28 papers considered the most relevant according to research questions is shown.