Exploiting multi-level parallel metaheuristics and heterogeneous computing to boost phylogenetics

Santander-Jiménez, Sergio; Vega‐Rodríguez, Miguel A.; Sousa, Leonel

doi:10.1016/j.future.2021.09.011

Cited by 3 publications

(1 citation statement)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Acknowledging this, Santander‐Jiménez et al. (2022) explore the combination of multilevel parallelism and heterogeneous computing. In particular, they describe a parallel metaheuristic, which establishes joint exploitation of parallel tasks at the algorithm, iteration, and solution levels.…”

Section: Phylogeneticsmentioning

confidence: 99%

On the role of metaheuristic optimization in bioinformatics

Calvet

Benito

Juan

et al. 2022

Int Trans Operational Res

View full text Add to dashboard Cite

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.

show abstract

Section: Phylogeneticsmentioning

confidence: 99%