Particle swarm optimization artificial intelligence technique for gene signature discovery in transcriptomic cohorts.

ABSTRACT: The development of gene signatures is key for delivering personalized medicine, despite only a few signatures being available for use in the clinic for cancer patients. Gene signature discovery tends to revolve around identifying a single signature. However, it has been shown that various highly predictive signatures can be produced from the same dataset. This study assumes that the presentation of top ranked signatures will allow greater efforts in the selection of gene signatures for validation on external datasets and for their clinical translation. Particle swarm optimization (PSO) is an evolutionary algorithm often used as a search strategy and largely represented as binary PSO (BPSO) in this domain. BPSO, however, fails to produce succinct feature sets for complex optimization proble

SUBMITTER: Murphy RG 

PROVIDER: S-EPMC9556859 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature