TCMGeneDIT: A database for associated traditional Chinese medicine, gene and disease infomation using text mining

Traditional Chinese Medicine (TCM), a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years. The fundamental principles of TCM are based on the Yin-Yang doctrine, the symbolic way of designating opposing forces, and the five element theory that everything in the Universe is dominated and balanced by the five elements, wood, fire, earth, metal and water (Chan K, 1995; Lu AP et al., 2004; Cheng JT, 2000). In recent years, it is known that many herbal medicines may be related to various symptoms or diseases and exhibit a variety of effects through direct or indirect interactions with different genes or protein such as the anti-inflammatory potential through the inhibition of cytokine, iNOS and COX-2 expression via NF-kappaB pathway (Hseu YC et al., 2005).

Text mining in biology is a deeper analysis of the literature to automatically extract specific information about genes, proteins and their functional associations (Krallinger M, Valencia A, 2005). As the rapid increases of TCM data, there is an urgent need to explore these resources effectively from the huge volume of literature (Feng Y et al., 2006). Over the past few years, several studies have been made on the mining or extraction of TCM information from literature. In addition, many databases have been developed for providing different aspects of TCM information but only few of them are published, presented with English, and freely accessible. However, to date, there has been no attempt to develop a database integrating information about TCM, genes and diseases using text mining.

We developed a database, TCMGeneDIT, providing association information about TCM, genes and diseases, relationships among effectors, TCM effects and effect receivers, and correlations between TCM and ingredients from vast amount of biomedical literature and information about protein-protein interactions and biological pathways from public databases. This database integrating TCM with life sciences and biomedical studies would facilitate the clinical research and the understanding of therapeutic mechanisms involved by TCM through inducing or suppressing the gene activities.

References:
1. Chan K: Progress in traditional Chinese medicine. Trends Pharmacol Sci 1995, 16(6):182-187.
2. Lu AP, Jia HW, Xiao C, Lu QP: Theory of traditional Chinese medicine and therapeutic method of diseases. World J Gastroenterol 2004, 10(13):1854-1856.
3. Cheng JT: Review: drug therapy in Chinese traditional medicine. J Clin Pharmacol 2000, 40(5):445-450.
4. Hseu YC, Wu FY, Wu JJ, Chen JY, Chang WH, Lu FJ, Lai YC, Yang HL: Anti-inflammatory potential of Antrodia Camphorata through inhibition of iNOS, COX-2 and cytokines via the NF-kappaB pathway. Int Immunopharmacol 2005, 5(13-14):1914-1925.
5. Krallinger M, Valencia A: Text-mining and information-retrieval services for molecular biology. Genome Biol 2005, 6(7):224.
6. Feng Y, Wu Z, Zhou X, Zhou Z, Fan W: Knowledge discovery in traditional Chinese medicine: state of the art and perspectives. Artif Intell Med 2006, 38(3):219-236.


© 2008 National Taiwan Univerisity, Taipei, Taiwan