Revealing new therapeutic opportunities through drug target prediction: a class imbalance-tolerant machine learning approach.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: In silico drug target prediction provides valuable information for drug repurposing, understanding of side effects as well as expansion of the druggable genome. In particular, discovery of actionable drug targets is critical to developing targeted therapies for diseases.

Authors

  • Siqi Liang
    Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA.
  • Haiyuan Yu
    Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA.