A novel hybrid framework for metabolic pathways prediction based on the graph attention network.

Journal: BMC bioinformatics
PMID: 36171550

Abstract

BACKGROUND: Making clear what kinds of metabolic pathways a drug compound involves in can help researchers understand how the drug is absorbed, distributed, metabolized, and excreted. The characteristics of a compound such as structure, composition and so on directly determine the metabolic pathways it participates in.

Authors

  • Zhihui Yang
    Institute of Artificial Intelligence, School of Computer Science, Wuhan University, China. Electronic address: zhy@whu.edu.cn.
  • Juan Liu
    Key State Laboratory of Software Engineering, School of Computer, Wuhan University, Wuhan 430072, PR China. Electronic address: liujuan@whu.edu.cn.
  • Hayat Ali Shah
    Institute of Artificial Intelligence, School of Computer Science, Wuhan University, China. Electronic address: hayatali@whu.edu.cn.
  • Jing Feng
    Department of Urology, ZhongNan Hospital, Wuhan University, No. 169 Donghu Road, Wuhan, Hubei, 430071, China.

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