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Research Interest

  • Genetic Network Modeling

    One important application of microarray data is genetic network modeling. Identify the network structure of genetic pathways, and the gene interaction relationships are important in understanding the regulation of gene expression, as well as the mechanism underlies complex traits. Our research efforts in this field including Bayesian networks, development of nonlinear correlation measures, and the incorporation of microarray data quality in network inference. More detail...

  • Mathematical Modeling in Diabetes

    Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion and/or insulin action. It is complex disease that involves the interplay of multiple genes and environmental factors. Our research include the mathematical modeling and simulation of islet function and insulin secretion, the glucose metabolic regulation, and the dynamics of disease pathogenesis. More detail...

  • Microarray Analysis

    Microarray is a technology that allows the profiling of genome-level gene expression changes. It holds great promise in dissecting the complex human diseases, and in understanding the gene expression regulatory mechanisms. Microarray data is often plagued with quality issues, and the analysis of microarray data is a formidable task. Our research has focused on the quantitative data quality control, data preprocessing including data filtering and normalization, as well as quality weighted statistics and data mining. These works have resulted in a microarray data analysis suite Matarray. More detail...