MRDDA: a multi-relational graph neural network for drug-disease association prediction.

Journal: Journal of translational medicine
Published Date: Jul 8, 2025

Abstract

BACKGROUND: Drug repositioning offers a promising avenue for accelerating drug development and reducing costs. Recently, computational repositioning approaches have gained attraction for identifying potential drug-disease associations (DDAs). Biological entities such as drugs, genes, proteins, RNA, and diseases interact within a complex network. How to adequately extract the intrinsic relationships among them and accurately predict the drug-disease associations remains a challenge.

Authors

  • Congzhou Chen
    College of Information Science and Technology, Beijing University of Chemical Technology, Beijing100029, China.
  • Yaozheng Zhou
    College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China.
  • Yinghong Li
    College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China.
  • Jin Xu
    Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, and School of Statistics, East China Normal University, Shanghai, China.
  • Demin Li
    the National Clinical Research Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, 100029, China. deminli2008@sina.com.
  • Lingfeng Wang
    School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China.

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