Metaheuristics for multiple sequence alignment: A systematic review. (October 2021)

• Record Type: Journal Article
• Authors: Amorim, Anderson Rici; Zafalon, Geraldo Francisco Donegá; Contessoto, Allan de Godoi; Valêncio, Carlos Roberto; Sato, Liria Matsumoto
• Is Part Of: Computational biology and chemistry. Volume 94(2021)
• Publication Date: 2021-10
• Subjects: Bioinformatics -- Multiple sequence alignment -- Metaheuristics -- Multi-objective optimization -- Systematic literature review; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2021.107563
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: 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. Graphical Abstract: ga1 Highlights: 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.