My research area is computational and systems biology. To elucidate the mechanism underlying biological processes, I use mathematical and computational approaches to model, simulate and analyze biological systems, specifically cellular sigaling transduction pathways. The biological systems I am working on are p53 and apoptosis pathway and circadian rhythm network. P53 is a critial tumor suppressor for human. We used mathematical model to reproduce experimental observation of p53 pulses in response to DNA damage and predict its behavior under different genetic perturbations. Our model predictions were validated by biochemical experiments of p53 responses in cancer cells as well as p53 gene transfected cells. These findings elucidated important mechanisms by which treatment such as radiation therapy can trigger programmed cell death of tumor. Circadian rhythm is a fundamental oscillatory biological process found in organisms ranging from insects, rodents, to humans. Using experimental assays, I have shown that the widely observed 24-hour circadian rhythm can be implemented by simple interactions of three key proteins. I have further developed quantitative models to characterize the dynamic interactions among components and identified key process for the rhythm.
My research interests include:
- Elucidate mechanisms underlying circadian rhythms in a model system using an integrated mathematical and experimental approach
- Mathematical modeling of protein-protein interaction in relationship to programmed cell death
- Robustness analysis of circadian rhythm and other oscillatory biological systems
- Applying control theory and dynamical systems theory to the studies of biological systems