TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

被引:122
作者
Fang, Yu-Ching [1 ]
Huang, Hsuan-Cheng [2 ,3 ]
Chen, Hsin-Hsi [4 ]
Juan, Hsueh-Fen [1 ,5 ,6 ,7 ]
机构
[1] Natl Taiwan Univ, Inst Mol & Cellular Biol, Taipei 10764, Taiwan
[2] Natl Yang Ming Univ, Inst Biomed Informat, Taipei 112, Taiwan
[3] Natl Yang Ming Univ, Ctr Syst & Synthet Biol, Taipei 112, Taiwan
[4] Natl Taiwan Univ, Dept Comp Sci & Informat Engn, Taipei 10764, Taiwan
[5] Natl Taiwan Univ, Dept Life Sci, Taipei 10764, Taiwan
[6] Natl Taiwan Univ, Grad Inst Biomed Elect & Bioinformat, Taipei 10764, Taiwan
[7] Natl Taiwan Univ, Ctr Syst Biol & Bioinformat, Taipei 10764, Taiwan
来源
BMC COMPLEMENTARY AND ALTERNATIVE MEDICINE | 2008年 / 8卷 / 1期
关键词
D O I
10.1186/1472-6882-8-58
中图分类号
R [医药、卫生];
学科分类号
10 [医学];
摘要
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 effecters 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.
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页数:11
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