We use a broad range of theoretical and computational techniques to study physical-chemical processes in the cell. In particular, we aim to develop computational models describing the dynamic and static heterogeneities of various cellular processes, from enzymatic catalysis to signal transduction.

Due to complexity of cell-biological events, a realistic modeling of these processes with purely physical techniques is very challenging. On the other hand, billions of years of evolution have lead to empirical answers to many difficult questions in physics and chemistry, such as designing a foldable protein or building a robust, yet sensitive signal transduction network. Bioinformatics helps us use this knowledge in a systematic manner. Thus, our approach is to merge constructively modern techniques in chemical physics and bioinformatics.

Students and postdoctoral research associates working in our group are exposed to diverse areas of protein modeling, bioinformatics, equilibrium and nonequilibrium statistical mechanics, polymer physics, and computational quantum chemistry.