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On the role of metaheuristic optimization in bioinformatics

Laura Calvet, Sergio Benito, Ángel A. Juan, Ferrán Prados

2022International Transactions in Operational Research25 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

MetaheuristicComputer scienceParallel metaheuristicInferenceField (mathematics)Optimization problemArtificial intelligenceMathematical optimizationData scienceMachine learningAlgorithmMeta-optimizationMathematicsPure mathematicsMetaheuristic Optimization Algorithms ResearchAdvanced Multi-Objective Optimization AlgorithmsEvolutionary Algorithms and Applications
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