Metabolomics Data Analysis in Traditional Chinese Medicine

The Data Science Discipline of the School of EECS is hosting the following guest seminar:
 

Speaker: Professor Qing Ye, Jiangxi University of Traditional Chinese Medicine

Abstract: Metabolomics of traditional Chinese medicine (TCM) provides crucial technical support for elucidating the holistic mechanisms of TCM, which involve multiple components, multiple targets, and multiple pathways. Addressing the characteristics of metabolomics data—such as high dimensionality, small sample sizes, high missingness, and strong correlations—this study systematically investigated data quality enhancement, stable screening of active drug components, and discovery of equivalent candidate component groups. This work established an integrated methodological framework spanning missing data handling, stable feature selection, and multi-group candidate solution analysis, which was validated using data from the classic formula Shenfu injection. Building on this foundation, we further developed an intelligent analysis platform for TCM metabolomics, offering methodological and tool-based support for research into the pharmacodynamic substance basis and mechanism of action of Chinese medicines.

The presentation will be given in Chinese. Non-Chinese speakers are welcome to use live translation apps.

Speaker: Professor Qing YE. She is Dean of the School of Intelligent Medicine and Information Engineering at Jiangxi University of Traditional Chinese Medicine.