​Research

    Research Expertise: Biomedical Informatics, Big Health Data (such as Electronic Health Records) Mining, Natural Language Processing, Biomolecular Network Modeling, Personalized Nutrition, and Multi-omics Data Analysis and Integration.

    Focusing on the "precise and systematic analysis of chronic disease risks", we develop artificial intelligence(AI) algorithms for multi - dimensional health big data by integrating, in an interdisciplinary manner, the concepts and methods of systems biology, natural language processing, and process control:

     1. To accurately identify the subtypes of chronic diseases. By analyzing the similarities and differences among these subtypes from multiple dimensions such as risk genes, physical examination indicators, and dietary factors, we design precise nutrition intervention measures specific to each subtype;

     2. To systematically analyze the associations among multiple diseases. We explain the concurrent risks of multiple diseases from aspects including gene pleiotropy, the correlation between genetic/environmental correlations, pleiotropic genes, shared gut microbiota, and dietary patterns, thus assisting in the joint prevention and management of comorbidities.