A robust fuzzy rule based integrative feature selection strategy for gene expression data in TCGA.

Journal: BMC medical genomics
Published Date: Jan 31, 2019

Abstract

BACKGROUND: Lots of researches have been conducted in the selection of gene signatures that could distinguish the cancer patients from the normal. However, it is still an open question on how to extract the robust gene features.

Authors

  • Shicai Fan
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China. shicaifan@uestc.edu.cn.
  • Jianxiong Tang
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China.
  • Qi Tian
    College of Biomedical Engineering and Instrument Science, Zhejiang University, Zheda Road, 310027 Hanghzou, China; Key Laboratory for Biomedical Engineering, Ministry of Education, China. Electronic address: Tianq@zju.edu.cn.
  • Chunguo Wu
    Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, China.

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