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Updated: Nov 24, 2025

Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
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FangNet: Mining herb hidden knowledge from TCM clinical effective formulas using structure network algorithm.

Dechao Bu1, Yan Xia2, JiaYuan Zhang2

  • 1Key Laboratory of Intelligent Information Processing, Advanced Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.

Computational and Structural Biotechnology Journal
|December 28, 2020
PubMed
Summary
This summary is machine-generated.

FangNet ranks herbs by importance in traditional formulas using network pharmacology. This aids discovering active ingredients from natural products for drug innovation.

Keywords:
CNKI, China National Knowledge InfrastructureEBM, Evidence-Based MedicineFOBT, Fecal Occult Blood TestFormulasHerbPDD, Phenotype-based Drug DiscoverySymptomTCMTCM, Traditional Chinese MedicineTHScore, Topological-Hub Score

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Area of Science:

  • Herbal Medicine
  • Network Pharmacology
  • Bioinformatics

Background:

  • Traditional Asian herbal formulas are valuable resources for drug discovery.
  • Identifying key herbs in complex multi-herb treatments is challenging.
  • Understanding herb roles is crucial for isolating bioactive compounds.

Purpose of the Study:

  • To develop a method for ranking herb importance in clinical formulas.
  • To facilitate the discovery of biologically active ingredients from natural products.
  • To create a collaborative platform for analyzing symptom-herb relationships.

Main Methods:

  • Constructed a symptom-herb network from clinical empirical prescriptions.
  • Applied the PageRank algorithm to rank herb topological importance.
  • Developed an interactive visualization for herb-herb co-occurrence and symptom associations.

Main Results:

  • FangNet platform ranks herbs based on their relative importance.
  • Provides insights into herb-herb co-occurrence and symptom associations.
  • Offers a secure, collaborative environment for analyzing clinical formulas.

Conclusions:

  • FangNet aids in identifying core herbs for active ingredient discovery.
  • The platform supports drug innovation by mining traditional herbal knowledge.
  • FangNet serves as a central hub for massive symptom-herb connections.