Computational Biology
Computational Biology is the newest of the department's four tracks for graduate education
and research. There are two faculty, David Green and Rob Rizzo who are biological
sciences PhDs using extensive mathematical modeling in their research. Carlos Simmerling
and Jin Wang in Chemistry are adjunct faculty who work closely with the Applied Math
computational biology group. A number of the faculty in the Computational Applied
Mathematics group have also worked on problems in biology, involving molecular dynamics,
organ modeling, and neural structure.
Evangelos Coutsias' research has focused on the modeling of nonlinear systems and continua, using techniques
of applied mathematics on problems motivated from applied physics, engineering and
biology. These include asymptotics and perturbation methods for the study of stability
and bifurcation phenomena in plasma physics, biology and fluid mechanics; high accuracy
numerical spectral methods for solving PDEs arising in continuum mechanics; and robust
numerical methods for systems of multivariate polynomials for the solution of problems
of inverse kinematics arising in molecular structure studies. His present work is
on the development of computational methods for the study of protein structure, especially
on the kinematic geometry of protein backbones subject to constraints. Current interests
focus on the refinement of protein structure and the development of computational
geometric methods for the efficient exploration of macromolecular shapespaces with
application to protein design and drug discovery. For more information, see Coutsias webpage.
David Green's research is focused on computational studies of protein interactions. Key areas include:
understanding the determinants of specificity in protein interactions through biomolecular
simulation; development and application of algorithms for the design of binding interfaces;
and development of tools for the study of protein-carbohydrate interactions, with
a focus on the glycobiology of HIV-1 infection. His research combines techniques from
applied mathematics and models from biophysical chemistry to solve important problems
in biology and medicine. For more information, see Green webpage.
Dima Kozakov's research interests lie at the intersection of applied mathematics, physics and computational
biology. He focuses on two main goals. The first is the development of mathematically
elegant, computationally efficient and physically accurate algorithms for modeling
macromolecular structure and function on the genome scale. The second is the application
of novel methods to improving the understanding of biological problems and to the
design of therapeutic molecules with desired biological and biomedical properties.
For more information, see
Kozakov webpage.
Robert Rizzo's research group seeks to understand the atomic basis for molecular recognition for
specific biological systems involved in human disease such as HIV/AIDS, cancer, and
influenza with the ultimate goal of developing new and improved drugs. Computational
methods are used to model how molecules interact at the atomic level with a given
drug target. The resultant 3D structural and energetic information is used to quantify
and rationalize drug-binding for known systems and to make new predictions. For more
information, see Rizzo webpage.