Prediction of drug-disease associations by integrating common topologies of heterogeneous networks and specific topologies of subnets.

Journal: Briefings in bioinformatics
Published Date:

Abstract

MOTIVATION: The development process of a new drug is time-consuming and costly. Thus, identifying new uses for approved drugs, named drug repositioning, is helpful for speeding up the drug development process and reducing development costs. Existing drug-related disease prediction methods mainly focus on single or multiple drug-disease heterogeneous networks. However, heterogeneous networks, and drug subnets and disease subnet contained in heterogeneous networks cover the common topology information between drug and disease nodes, the specific information between drug nodes and the specific information between disease nodes, respectively.

Authors

  • Ling Gao
  • Hui Cui
    Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, 1278 Keyuan Road, Shanghai 201203, PR China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, PR China.
  • Tiangang Zhang
    School of Mathematical Science, Heilongjiang University, Harbin 150080, China. zhang@hlju.edu.cn.
  • Nan Sheng
    School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China.
  • Ping Xuan
    School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China.