Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

TCM

General information

URL: http://tcm.lifescience.ntu.edu.tw
Full name: Traditional Chinese Medicine
Description: TCMGeneDIT is a database system providing association information about traditional Chinese medicines (TCMs), genes, diseases, TCM effects and TCM ingredients automatically mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information collected from public databases are also available. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in deducing possible synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. TCMGeneDIT is a unique database of various association information about TCMs. The database integrating TCMs with life sciences and biomedical studies would facilitate the modern clinical research and the understanding of therapeutic mechanisms of TCMs and gene regulations.
Year founded: 2008
Last update:
Version:
Accessibility:
Manual:
Accessible
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Country/Region: China

Classification & Tag

Data type:
Data object:
Database category:
Major species:
NA
Keywords:

Contact information

University/Institution: National Taiwan University
Address:
City:
Province/State: Taiwan
Country/Region: China
Contact name (PI/Team): Fang YC
Contact email (PI/Helpdesk): yukijuan@ntu.edu.tw

Publications

18854039
TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining. [PMID: 18854039]
Fang YC, Huang HC, Chen HH, Juan HF.

BACKGROUND: Traditional Chinese Medicine (TCM), a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature.
METHODS: TCM, gene, disease, biological pathway and protein-protein interaction information were collected from public databases. For association discovery, the TCM names, gene names, disease names, TCM ingredients and effects were used to annotate the literature corpus obtained from PubMed. The concept to mine entity associations was based on hypothesis testing and collocation analysis. The annotated corpus was processed with natural language processing tools and rule-based approaches were applied to the sentences for extracting the relations between TCM effectors and effects.
RESULTS: We developed a database, TCMGeneDIT, to provide association information about TCMs, genes, diseases, TCM effects and TCM ingredients mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information are also available for exploring the regulations of genes associated with TCM curative effects. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in understanding the possible therapeutic mechanisms of TCMs via gene regulations and deducing synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. The database is now available at http://tcm.lifescience.ntu.edu.tw/.
CONCLUSION: TCMGeneDIT is a unique database that offers diverse association information on TCMs. This database integrates TCMs with biomedical studies that would facilitate clinical research and elucidate the possible therapeutic mechanisms of TCMs and gene regulations.

BMC Complement Altern Med. 2008:8() | 48 Citations (from Europe PMC, 2024-05-11)

Ranking

All databases:
2566/6000 (57.25%)
Expression:
524/1143 (54.243%)
Interaction:
436/982 (55.703%)
Health and medicine:
582/1394 (58.321%)
2566
Total Rank
46
Citations
2.875
z-index

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Record metadata

Created on: 2018-01-28
Curated by:
Lin Liu [2022-08-11]
Mengyu Pan [2018-09-21]
Mengyu Pan [2018-02-23]
Pei Wang [2018-01-27]