My research interests encompass both experimental and theoretical treatment of mathematical models, particularly those applied to biopolymers such as DNA. This work stems from my biochemical, biophysical, and computational training, and many of the scientific tools I employ are generalizable to other areas of biochemical research. Some noteworthy examples of mathematical and biophysical collaborative projects, both internally and extramurally, include: (1) mathematical modeling of enzyme kinetics (e.g. in vitro T4 DNA ligase-catalyzed cyclization kinetics), (2) developing and experimentally validating thermodynamic and statistical mechanical models (e.g. looping of the lac operon in E. coli cells), (3) developing and implementing image processing software for atomic force microscopy images of DNA molecules, (4) experimental and theoretical investigations of biodistribution and pharmacokinetics of a therapeutic ‘drug’ in a mouse model of multiple sclerosis, (5) nonlinear least-squares curve fitting and parameter estimation (e.g. from polymer models of DNA like the wormlike chain model, from thermodynamic models of looping, from dose-response curves, from binding affinity data, etc.), (6) exploring the role of DNA bending proteins in facilitating the formation of DNA loops, (7) examining the role of electrostatic charge and shape in determining electrophoretic mobility of biopolymers, and (8) ongoing computational analysis of massive datasets containing thousands of in vitro selections of RNA libraries against various protein targets, requiring extensive use of computer clusters for data management and analysis.
