Alzheimer's disease knowledge graph enhances knowledge discovery and disease prediction.

Journal: Computers in biology and medicine
Published Date: Apr 29, 2025

Abstract

OBJECTIVE: To construct an Alzheimer's Disease Knowledge Graph (ADKG) by extracting and integrating relationships among Alzheimer's disease (AD), genes, variants, chemicals, drugs, and other diseases from biomedical literature, aiming to identify existing treatments, potential targets, and diagnostic methods for AD.

Authors

  • Yue Yang
    Department of Nephrology, China-Japan Friendship Hospital, Beijing 100029, China.
  • Kaixian Yu
    Insilicom LLC, Tallahassee FL, USA.
  • Shan Gao
    Department of Mathematics and Statistics, Yunnan University, China.
  • Sheng Yu
    Medical College, Guangxi University of Science and Technology, Liuzhou, Guangxi, 545005, China.
  • Di Xiong
    Department of Mathematics, Shanghai University, China.
  • Chuanyang Qin
    Department of Mathematics and Statistics, Yunnan University, China.
  • Huiyuan Chen
    Department of Mathematics and Statistics, Yunnan University, China.
  • Jiarui Tang
    Department of Biostatistics, University of North Carolina at Chapel Hill, USA.
  • Niansheng Tang
    Department of Mathematics and Statistics, Yunnan University, China.
  • Hongtu Zhu
    Department of Biostatistics, University of North Carolina at Chapel Hill, USA. Electronic address: htzhu@email.unc.edu.

Keywords

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