Abstract
Network pharmacology is a research method based on biological information data and networks, which can reveal the mechanism of action of Traditional Chinese Medicine, and then discover more active substances with therapeutic effects. However, most of the existing TCM databases lack the collection of TCM prescription data and in-depth data mining and visualization for both TCM and its related information, leading to a limited support in network pharmacology research. In this paper we have constructed Traditional Chinese Medicine Information Database Platform (TCMIDP) for network pharmacology research. It is composed of TCM composition information database and Web-based built-in TCM network pharmacology module. The TCM composition information database collects hierarchical data which contains 4 kinds of TCM resource entities and 6 kinds of associations. In the Web-based TCM network pharmacology module, a visual interactive network diagram displays the data entities and their associations. To mine the TCM data in the above database, node mining and clustering analyses are provided for users to do network pharmacology research. The analyses result, coupled with the visual interactive network diagram can help exploring the 4 types of TCM resource entities that have key regulatory functions in the integrated information network of TCM. TCMIDP makes a significant contribution to data collection, data mining and visualization analysis of TCM, and provides more valuable information support for network pharmacology research.
Supported by Important Drug Development Fund, Ministry of Science and Technology of China (2018ZX09735002).
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Ye, L., Liu, W., Zheng, Y., Li, J. (2024). TCMIDP: A Comprehensive Database of Traditional Chinese Medicine for Network Pharmacology Research. In: Strauss, C., Amagasa, T., Manco, G., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2024. Lecture Notes in Computer Science, vol 14910. Springer, Cham. https://doi.org/10.1007/978-3-031-68309-1_3
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DOI: https://doi.org/10.1007/978-3-031-68309-1_3
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