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Related Experiment Video

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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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HerbKG: Constructing a Herbal-Molecular Medicine Knowledge Graph Using a Two-Stage Framework Based on Deep Transfer

Xian Zhu1,2, Yueming Gu3, Zhifeng Xiao4

  • 1School of Information Management, Nanjing University, Nanjing, China.

Frontiers in Genetics
|May 16, 2022
PubMed
Summary

This study introduces HerbKG, a novel knowledge graph connecting herbal and molecular medicine. HerbKG organizes key information on herbs, chemicals, genes, and diseases to advance evidence-based herbal medicine.

Keywords:
BERTbiobertchemicaldiseasegeneherbknowledge graphontology

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Area of Science:

  • Integrative medicine
  • Bioinformatics
  • Computational biology

Background:

  • Herbalism studies are increasingly using scientific approaches, but findings are disorganized.
  • Current herbal knowledge graphs lack connections to molecular medicine.

Purpose of the Study:

  • To develop HerbKG, a knowledge graph bridging herbal and molecular medicine.
  • To systematically organize herbal-molecular domain knowledge for improved discovery and application.

Main Methods:

  • Developed a learning framework to automate knowledge graph construction.
  • Analyzed over 500,000 PubMed abstracts to populate the knowledge graph.

Main Results:

  • Created HerbKG, a knowledge graph linking herbs, chemicals, genes, and diseases.
  • Populated HerbKG with 53,000 relations, establishing herbal-molecular connections.

Conclusions:

  • HerbKG provides a comprehensive resource for herbal-molecular domain knowledge.
  • Facilitates downstream applications in evidence-based herbal medicine development.