The recent technological advances in molecular biology forces us to take a
more quantitative take on the subject. Mathematical and physical approaches in
biology cover a wide variety of topics. They incorporate well established
disciplines like molecular biophysics and structural biology to resurgent areas
like system level dynamical analysis of biochemical networks.
We use computer simulations and statistical mechanics to study thestructure, function, folding, and dynamics of proteins. Current researchprojects include the study of mechanisms for molecular recognition byproteins, homology modeling, and protein dynamics on longer time scales.We are interested in the interplay between computational models andexperimental studies of biological assemblies at different levels ofresolution. We are engaged in research in the area of ComputationalMolecular Biology - including the development of computational tools whichwill be useful for predicting the functions and structures of newlysequenced genes, as well as for studying the basic physical principles ofprotein folding.
Our research combines a variety of computational approaches (e.g.,Metropolis-Monte Carlo, energy minimization, polymer statistical mechanics,normal mode analysis) with developments in polymer theory to study thesequence,structure, properties, and function of nucleic acids at different levels ofresolution. Problems of current interest include: elastic models of the longthreadlike DNA double helix that account for its local structure, directrecognition, mesoscopic looping, supercoiling and knotting; conformationalchanges, including the overstretching and overtwisting of single molecules;electrostatic effects governing macromolecular structure and recognition;interactions with proteins, drugs, and carcinogens.
Our research aims to understand information processing in the cellular enviroment. We are mostly focused on studying signaling and transcription. Our interests range from information theory of signaling cascades to bioinformatic tools for discovery of the transcriptional networks that affect gene expression as a result signaling events. We are also analyzing bistable genetic systems that can hold two different states for the same external cue. Currently, to complement our computational and theoretical work, we have set up a wet lab in the Waksman Institute to test our predictions and to generate data for further model building.
Revised September, 2006