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Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, plays an important role in maintaining the health of peoples of Asia, and is gaining more and more application all over the world. However, owing to the diversity of TCM’s ingredients and the complexity of TCM’s interaction with human body, it is still quite difficult to uncover the underlying molecular mechanism of TCM. The clarification of the TCM’s molecular mechanism has become a bottleneck in TCM modernization and internationalization. BATMAN-TCM (a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine) is the first online bioinformatics analysis tool specially designed for the research of molecular mechanism of TCM.
For user-submitted TCM, BATMAN-TCM will first predict potential targets for each query TCM’s ingredient, and then perform functional analyses on these targets including Gene Ontology (GO) term, KEGG pathway and OMIM/TTD disease enrichment analyses. TCM ingredient-target-pathway/disease association network and biological pathway with highlighted TCM’s targets will also be shown. These functions aim to contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM and to provide clues for the following experimental validation. In addition, BATMAN-TCM also supports users to simultaneously input multiple TCMs, which is typically used to simultaneously analyze multiple compositive herbs of a formula, helping understand this combinational principle of a formula from molecular and systematic level.
Please see “Tutorials” for more information.
Every user’s submitted data will be kept private and not viewable by anyone other than the user or those given permission by the user.
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Please cite: Kong X, Liu C, Zhang Z, Cheng M, Mei Z, Li X, Liu P, Diao L; Ma Y, Jiang P; Kong X, Nie S, Guo Y, Wang Z, Zhang X, Wang Y, Tang L, Guo S, Liu Z, Li D. BATMAN-TCM 2.0: an enhanced integrative database for known and predicted linkages between traditional Chinese medicine ingredients and target proteins. Nucleic Acids Research. (10.1093/nar/gkad926)
 
Contact: Zhongyang Liu, liuzy1984@163.com, Beijing Proteome Research Center, Beijing, China.