Traditional Chinese Medicine Multidimensional Knowledge Graph

Overview of the Traditional Chinese Medicine Multi-dimensional Knowledge Graph (TCM-MKG)

The Traditional Chinese Medicine Multi-dimensional Knowledge Graph (TCM-MKG) is a comprehensive, open-source data platform developed by Jingqi Zeng in November 2024. This platform aims to integrate and standardize a vast array of data from multiple sources, encompassing both traditional Chinese medicine (TCM) and modern biomedical sciences. By organizing and linking this diverse information, TCM-MKG acts as a bridge that connects the ancient wisdom of TCM with contemporary medical research and applications.

Key Features and Objectives:

Multi-source Data Integration: TCM-MKG consolidates data from over 30 authoritative resources, covering a broad spectrum of topics, including TCM terminology, Chinese patent medicines (CPM), Chinese herbal pieces (CHP), natural products (NP), chemical components, disease targets, and more. These data sources are carefully curated and interlinked, ensuring a rich, multi-dimensional view of TCM in relation to modern biomedical research. The platform incorporates data from reputable databases such as DrugBank, BioGRID, DisGeNET, STRING, and many others, ensuring that the TCM knowledge is not only expansive but also scientifically robust and cross-referenced with global biomedical standards.

Standardized Design for Global Interoperability: TCM-MKG adheres to international data standards and integrates with widely-used global medical classification systems such as ICD-11, UMLS, MeSH, and DOID. This ensures that the platform’s data is globally comparable and facilitates easy integration with international research efforts, promoting collaboration and knowledge exchange across the fields of TCM and modern medicine.

Open Source and Collaborative: In line with its mission to enhance transparency and accessibility, TCM-MKG is open-sourced in a structured tabular format. This allows researchers worldwide to freely access, contribute to, and expand upon the data, fostering interdisciplinary collaboration and accelerating innovation in both TCM research and modern medicine.

Advanced Analytical Capabilities: By leveraging the power of knowledge graph technology and graph-based intelligence algorithms, TCM-MKG supports deep data mining and relational reasoning. Researchers can uncover hidden associations between TCM components, diseases, and targets, providing insights into the mechanisms of herbal interactions and offering new pathways for drug discovery and therapeutic research.

Personal Research Application:

Using the TCM-MKG platform, I conducted a study titled "Graph Neural Networks for Quantifying Compatibility Mechanisms in Traditional Chinese Medicine." This research applied advanced graph intelligence algorithms to quantitatively assess the compatibility mechanisms of Chinese herbal formulas. The study provides fresh insights into the underlying principles of TCM herbal combinations.

This research has been published as a preprint on ArXiv:

Zeng, J., & Jia, X. (2024). Graph Neural Networks for Quantifying Compatibility Mechanisms in Traditional Chinese Medicine. ArXiv. https://arxiv.org/abs/2411.11474

The code and methodology for this research have been open-sourced and are available on GitHub.

Acknowledgments:

I would like to express my deep gratitude to the contributors and organizations that have made their data freely available for this project. The integration of diverse data sources such as those from the World Health Organization (WHO), NCBI, DrugBank, BioGRID, and many others has been essential in creating a comprehensive and multi-dimensional resource. Their commitment to open access and data sharing has greatly enriched the TCM-MKG platform and enabled the exploration of novel research directions that bridge traditional and modern scientific knowledge.

Contact Information:

For further inquiries or more detailed information, please feel free to contact:Email: [e-mail]