A Nested Genetic Algorithm for feature selection in high-dimensional cancer Microarray datasets

作者：

Highlights：

• Feature selection over high-dimensional colon cancer Microarray Datasets.

• Features selected from both Gene Expression and DNA-Methylation Microarray datasets.

• Resultant six biomarker genes for colon cancer validated using Enrichment Analysis.

• Biomarker genes validated on independent datasets with 99.9% classification accuracy.

摘要

•Feature selection over high-dimensional colon cancer Microarray Datasets.•Features selected from both Gene Expression and DNA-Methylation Microarray datasets.•Resultant six biomarker genes for colon cancer validated using Enrichment Analysis.•Biomarker genes validated on independent datasets with 99.9% classification accuracy.

论文关键词：Microarray gene expression,DNA Methylation,Colon cancer,Lung cancer,Machine learning,Genetic algorithm,Feature selection,Support Vector Machine

论文评审过程：Received 18 March 2018, Revised 18 October 2018, Accepted 14 December 2018, Available online 14 December 2018, Version of Record 20 December 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.022