SZBC-AI4TCM: a comprehensive web-based computing platform for traditional Chinese medicine research and development

Area of Science:

• Computational biology
• Bioinformatics
• Traditional Chinese Medicine research

Background:

• Traditional Chinese Medicine (TCM) research faces challenges due to increasing data complexity and volume.
• Conventional experimental methods are inadequate for modern TCM development.
• Expertise in programming, AI, and bioinformatics is often required, posing barriers for many researchers.

Purpose of the Study:

• To develop a user-friendly, web-based computing platform for comprehensive TCM data analysis.
• To accelerate TCM research and reduce associated costs through AI and bioinformatics integration.
• To embody the "ShuZhiBenCao" (Digital Herbal) concept using artificial intelligence.

Main Methods:

• Development of SZBC-AI4TCM, a comprehensive web-based computing platform.
• Integration of advanced AI algorithms (machine learning, deep learning) and bioinformatics tools.
• Implementation of an intuitive visual interface with hardware-software acceleration.

Main Results:

• The platform enables end-to-end analysis, including TCM formulation, mechanism elucidation, and drug screening.
• SZBC-AI4TCM allows researchers without computational backgrounds to perform efficient and accurate analyses.
• Demonstrated functionalities and analytical capabilities using TCM research in Alzheimer's disease as a case study.

Conclusions:

• SZBC-AI4TCM provides robust computational support, enhancing efficiency and reducing costs in TCM research.
• The platform offers novel approaches for studying complex TCM systems, advancing TCM modernization.
• SZBC-AI4TCM is poised to play a significant role in future TCM research, interdisciplinary collaboration, and global health initiatives.