TCMKD: From ancient wisdom to modern insights-A comprehensive platform for traditional Chinese medicine knowledge discovery
Wenke Xiao, Mengqing Zhang, Danni Zhao, Fanbo Meng, Qiang Tang, Lianjiang Hu, Hongguo Chen, Yixi Xu, Qianqian Tian, Mingrui Li, Guiyang Zhang, Liang Leng, Shilin Chen, Chi Song, Wei Chen
Abstract
Traditional Chinese medicine (TCM) serves as a treasure trove of ancient knowledge, holding a crucial position in the medical field. However, the exploration of TCM's extensive information has been hindered by challenges related to data standardization, completeness, and accuracy, primarily due to the decentralized distribution of TCM resources. To address these issues, we developed a platform for TCM knowledge discovery (TCMKD, https://cbcb.cdutcm.edu.cn/TCMKD/ ). Seven types of data, including syndromes, formulas, Chinese patent drugs (CPDs), Chinese medicinal materials (CMMs), ingredients, targets, and diseases, were manually proofread and consolidated within TCMKD. To strengthen the integration of TCM with modern medicine, TCMKD employs analytical methods such as TCM data mining, enrichment analysis, and network localization and separation. These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights. In addition to its analytical capabilities, a quick question and answer (Q&A) system is also embedded within TCMKD to query the database efficiently, thereby improving the interactivity of the platform. The platform also provides a TCM text annotation tool, offering a simple and efficient method for TCM text mining. Overall, TCMKD not only has the potential to become a pivotal repository for TCM, delving into the pharmacological foundations of TCM treatments, but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems, extending beyond just TCM. • TCMKD consolidated massive amounts of TCM data that has been manually quality-checked. • TCMKD integrated diverse computational tools for comprehensive TCM data annotation and mining. • TCMKD applied network algorithms to elucidate drug-disease connections within the human protein interactome. • TCMKD integrated a Neo4j-based knowledge graph and Q&A system, facilitating TCM data retrieval and user interaction.