A Cancer Gene Selection Algorithm Based on the K-S Test and CFS.

Journal: BioMed research international
Published Date: May 8, 2017

Abstract

BACKGROUND: To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S) test and correlation-based feature selection (CFS) principles. The algorithm selects distinguished genes first using the K-S test, and then, it uses CFS to select genes from those selected by the K-S test.

Authors

  • Qiang Su
    Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
  • Yina Wang
    Department of VIP Medical Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China.
  • Xiaobing Jiang
    College of Life Sciences, Henan Normal University, Xinxiang, China.
  • Fuxue Chen
    College of Life Sciences, Shanghai University, Shanghai 2000444, China.
  • Wen-Cong Lu
    Department of Chemistry, College of Sciences, Shanghai University, Shanghai 200444, China.

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