SymMap
SymMap integrates traditional Chinese medicine herbs, symptoms, diseases, ingredients, and target genes to map clinical phenotypes to molecular targets for applications such as phenotypic drug discovery.
Key Features:
- Extensive Database Content: Contains 499 herbs, 19,595 constituent ingredients, 1,717 TCM symptoms mapped to 961 corresponding modern symptom terms, 5,235 diseases, and 4,302 target genes.
- Symptom Mapping: Maps TCM symptoms to modern medical symptom terms with curation by a committee of 17 TCM experts.
- Disease and Target Associations: Records symptom–disease relationships and ingredient–target interactions linking herbs and ingredients to diseases and 4,302 genes.
- Heterogeneous Network Construction: Integrates herbs, ingredients, symptoms, diseases, and target genes into a large heterogeneous network for joint phenotypic and molecular analysis.
- Inference of Relationships: Applies statistical tests to infer pairwise relationships among components for ranking and filtering candidate leads.
Scientific Applications:
- Phenotypic Drug Discovery: Links phenotype changes and mapped symptoms to herbal ingredients and molecular targets to support phenotypic screening and lead identification.
- Therapeutic Hypothesis Generation: Enables exploration of relationships among herbs, ingredients, target genes, symptoms, and diseases to generate candidate therapeutic leads and mechanistic hypotheses.
Methodology:
Curated mappings of TCM symptoms to modern symptom terms by 17 experts; compilation of herb–ingredient, ingredient–target, and symptom–disease relationships; integration of all components into a heterogeneous network; application of statistical tests to infer pairwise relationships.
Topics
Collections
Details
- Tool Type:
- web application
- Added:
- 1/20/2021
- Last Updated:
- 5/21/2021
Operations
Publications
Wu Y, Zhang F, Yang K, Fang S, Bu D, Li H, Sun L, Hu H, Gao K, Wang W, Zhou X, Zhao Y, Chen J. SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping. Nucleic Acids Research. 2018;47(D1):D1110-D1117. doi:10.1093/nar/gky1021. PMID:30380087. PMCID:PMC6323958.