1.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
Journal of Pharmaceutical Analysis 2025;15(6):101297-101297
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.
2.The Genome Sequence Archive Family:Toward Explosive Data Growth and Diverse Data Types
Chen TINGTING ; Chen XU ; Zhang SISI ; Zhu JUNWEI ; Tang BIXIA ; Wang ANKE ; Dong LILI ; Zhang ZHEWEN ; Yu CAIXIA ; Sun YANLING ; Chi LIANJIANG ; Chen HUANXIN ; Zhai SHUANG ; Sun YUBIN ; Lan LI ; Zhang XIN ; Xiao JINGFA ; Bao YIMING ; Wang YANQING ; Zhang ZHANG ; Zhao WENMING
Genomics, Proteomics & Bioinformatics 2021;19(4):578-583
The Genome Sequence Archive (GSA) is a data repository for archiving raw sequence data, which provides data storage and sharing services for worldwide scientific communities. Considering explosive data growth with diverse data types, here we present the GSA family by expanding into a set of resources for raw data archive with different purposes, namely, GSA (https://ngdc.cncb.ac.cn/gsa/), GSA for Human (GSA-Human, https://ngdc.cncb.ac.cn/gsa-human/), and Open Archive for Miscellaneous Data (OMIX, https://ngdc.cncb.ac.cn/omix/). Compared with the 2017 version, GSA has been significantly updated in data model, online functionalities, and web interfaces. GSA-Human, as a new partner of GSA, is a data repository specialized in human genetics-related data with controlled access and security. OMIX, as a critical complement to the two resources mentioned above, is an open archive for miscellaneous data. Together, all these resources form a family of resources dedicated to archiving explosive data with diverse types, accepting data submissions from all over the world, and providing free open access to all publicly available data in support of worldwide research activities.

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