LTM-TCM

LTM-TCM integrates Traditional Chinese Medicine data with biomedical knowledge to enable network pharmacology analyses, bioactive ingredient screening, target prediction, and mechanism prediction for modern biomedical research.

Key Features:

• Extensive Data Integration: Integrates high-quality data from fourteen authoritative TCM databases and incorporates 41,025 manually collected clinical treatment records and 213 ancient Chinese medical texts.
• Advanced Biomedical Natural Language Processing (BioNLP): Employs in-house BioNLP techniques to extract and correct relationships among symptoms, prescriptions, herbs, ingredients, and biological targets from a corpus of over 30 million articles.
• Cross-Field Research Pipelines: Provides analytical pipelines for bioactive ingredient screening, target prediction, and mechanism prediction at molecular and phenotypic levels.

Scientific Applications:

• Drug discovery and pharmacological research: Supports discovery and pharmacological studies using a comprehensive dataset containing 1,928 symptoms, 48,126 prescriptions, 9,122 plants, 34,967 ingredients, 13,109 targets, and 1,170,133 interactions among TCM components.
• Mechanism and target exploration: Enables exploration of molecular mechanisms underlying TCM practices and prediction/validation of target–compound relationships.

Methodology:

Applies network pharmacology principles combined with advanced data integration and in-house BioNLP techniques (using a corpus of over 30 million articles) to extract and correct interactions among TCM entities.