Cancer subtype prediction from a pathway-level perspective by using a support vector machine based on integrated gene expression and protein network.

Journal: Computer methods and programs in biomedicine
Published Date: Jan 20, 2017

Abstract

BACKGROUND AND OBJECTIVE: Distinguishing cancer subtypes is critical for selecting the appropriate treatment strategy. Bioinformatics approaches have gradually taken the place of clinical observations and pathological experiments. However, these approaches are typically only used in gene expression profiling. Previous studies have primarily focused on the gene level or specific diseases, and thus pathway-level factors have not been considered. Therefore, a computational method that integrates gene expression and pathway is necessary.

Authors

  • Fei-Hung Hung
    Graduate Institute of Biomedical Informatics, Taipei Medical University, 250 Wu-Hsing Street, Taipei 11031, Taiwan.
  • Hung-Wen Chiu
    Graduate Institute of Biomedical Informatics, Taipei Medical University, 250 Wu-Hsing Street, Taipei City, Taiwan. Electronic address: hwchiu@tmu.edu.tw.

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