ClearF: a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction.

Journal: BMC medical genomics
Published Date:

Abstract

BACKGROUND: Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information-theoretic approaches. However, most of these methods generally require a long processing time. In addition, information-theoretic methods discretize continuous features, which is a drawback that can lead to the loss of information.

Authors

  • Sehee Wang
    Department of Computer Engineering, Ajou University, Suwon, 16499, South Korea.
  • Hyun-Hwan Jeong
    Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, 77030, USA.
  • Kyung-Ah Sohn
    Department of Artificial Intelligence, Ajou University, Suwon, South Korea.