Integrating specific and common topologies of heterogeneous graphs and pairwise attributes for drug-related side effect prediction.

Journal: Briefings in bioinformatics
Published Date: May 13, 2022

Abstract

MOTIVATION: Computerized methods for drug-related side effect identification can help reduce costs and speed up drug development. Multisource data about drug and side effects are widely used to predict potential drug-related side effects. Heterogeneous graphs are commonly used to associate multisourced data of drugs and side effects which can reflect similarities of the drugs from different perspectives. Effective integration and formulation of diverse similarities, however, are challenging. In addition, the specific topology of each heterogeneous graph and the common topology of multiple graphs are neglected.

Authors

  • Ping Xuan
    School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China.
  • Meng Wang
    State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150001, China.
  • Yong Liu
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.
  • Dong Wang
    Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
  • Tiangang Zhang
    School of Mathematical Science, Heilongjiang University, Harbin 150080, China. zhang@hlju.edu.cn.
  • Toshiya Nakaguchi

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