Optimization of Gene Selection for Cancer Classification in High-Dimensional Data Using an Improved African Vultures Algorithm

• Published in: Algorithms Vol. 17; no. 8; p. 342
• Main Authors: Gafar, Mona G., Abohany, Amr A., Elkhouli, Ahmed E., El-Mageed, Amr A. Abd
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2024
• Subjects: Accuracy; African vultures algorithm; Algorithms; Biomarkers; Cancer; Classification; Datasets; Deoxyribonucleic acid; differential evolution; Dimensional analysis; DNA; Evolutionary computation; Feature selection; Gene expression; gene selection; Gene sequencing; Genes; Genetic aspects; Genetic markers; Genetic transcription; Heuristic; Heuristic methods; high dimensionality; Investigations; Mathematical optimization; meta-heuristic algorithms; Methods; Optimization; Random variables; Ribonucleic acid; RNA; RNA sequencing; Support vector machines; Saudi Arabia

This study presents a novel method, termed RBAVO-DE (Relief Binary African Vultures Optimization based on Differential Evolution), aimed at addressing the Gene Selection (GS) challenge in high-dimensional RNA-Seq data, specifically the rnaseqv2 lluminaHiSeq rnaseqv2 un edu Level 3 RSEM genes normali...