A multi-objective optimization approach for the identification of cancer biomarkers from RNA-seq data
作者：
Highlights：
• A new gene selection method for cancer biomarker identification has been developed.
• The method combines feature selection, SVM, and ABCD algorithm.
• The evaluation has been performed with five RNA-seq cancer datasets.
• Comparisons have been done with five gene selection methods from other authors.
• The biological relevance has been analysed, showing the good results of the proposal.
摘要
•A new gene selection method for cancer biomarker identification has been developed.•The method combines feature selection, SVM, and ABCD algorithm.•The evaluation has been performed with five RNA-seq cancer datasets.•Comparisons have been done with five gene selection methods from other authors.•The biological relevance has been analysed, showing the good results of the proposal.
论文关键词：Multi-objective optimization,Evolutionary computation,Support vector machine,Cancer,Biomarker,RNA-seq
论文评审过程：Received 23 April 2020, Revised 21 May 2021, Accepted 26 December 2021, Available online 11 January 2022, Version of Record 17 January 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.116480
