Recursive Memetic Algorithm for gene selection in microarray data

作者：

Highlights：

• Development of a gene selection algorithm for identification of biomarkers from microarray data.

• Application of the method on seven widely used datasets.

• Validation of the genes obtained here using different metrics such as box-plots, heat maps among others.

• Reporting of biological significance of the genes through Gene Ontology and KEGG pathways.

• Citation of work showing obtained genes’ status as biomarkers.

摘要

•Development of a gene selection algorithm for identification of biomarkers from microarray data.•Application of the method on seven widely used datasets.•Validation of the genes obtained here using different metrics such as box-plots, heat maps among others.•Reporting of biological significance of the genes through Gene Ontology and KEGG pathways.•Citation of work showing obtained genes’ status as biomarkers.

论文关键词：Recursive memetic algorithm,Gene selection,Microarry data,Biomarker,Cancer classification

论文评审过程：Received 17 January 2018, Revised 17 May 2018, Accepted 22 June 2018, Available online 11 July 2018, Version of Record 18 September 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.06.057