On the role of metaheuristic optimization in bioinformatics

Laura Calvet*, Sergio Benito, Angel A. Juan, Ferran Prados

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Metaheuristic algorithms are employed to solve complex and large-scale optimization problems in many different fields, from transportation and smart cities to finance. This paper discusses how metaheuristic algorithms are being applied to solve different optimization problems in the area of bioinformatics. While the text provides references to many optimization problems in the area, it focuses on those that have attracted more interest from the optimization community. Among the problems analyzed, the paper discusses in more detail the molecular docking problem, the protein structure prediction, phylogenetic inference, and different string problems. In addition, references to other relevant optimization problems are also given, including those related to medical imaging or gene selection for classification. From the previous analysis, the paper generates insights on research opportunities for the Operations Research and Computer Science communities in the field of bioinformatics.

Original languageEnglish
Pages (from-to)2909-2944
Number of pages36
JournalInternational Transactions in Operational Research
Volume30
Issue number6
DOIs
Publication statusPublished - Nov 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • bioinformatics
  • combinatorial optimization
  • metaheuristics

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