MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks.

Journal: BMC bioinformatics
Published Date: Jan 13, 2025

Abstract

BACKGROUND: MicroRNAs (miRNAs) are pivotal in the initiation and progression of complex human diseases and have been identified as targets for small molecule (SM) drugs. However, the expensive and time-intensive characteristics of conventional experimental techniques for identifying SM-miRNA associations highlight the necessity for efficient computational methodologies in this field.

Authors

  • Jianwei Li
    School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China.
  • Xukun Zhang
    School of Artificial Intelligence, Hebei University of Technology, 300401, Tianjin, China.
  • Bing Li
  • Ziyu Li
    Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
  • Zhenzhen Chen
    Second Affiliated Hospital of Army Medical University (Xinqiao Hospital), No.83, Xinqiao Zheng Road, 400037 Chongqing, China.

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