Current Center Participants
and Research Interests
William
Atchley
William Neal Reynolds Professor
of Genetics and Statistics and
Director of the Center for Computational Biology
My research focuses on exploring broad questions in molecular evolution,
proteomics, and developmental quantitative genetics. One project involves
studies on the origin, evolution and structure of the basic helix-loop-helix
(bHLH) family of proteins, which are transcriptional regulators involved
in a diverse array of developmental processes. We are particularly interested
in understanding multidimensional covariation among amino acids and its
relationship to protein structure and evolution. A second project concerns
studies of the genetic architecture of complex developmental traits in
the mouse.
Carla
Mattos
Assistant Professor of Molecular
and Structural Biochemistry
The
focus of our research is the study of binding sites on the surfaces of
Ras GTPases, a family of proteins central to signal transduction pathways
in the cell. These signaling pathways lead to a variety of critical biological
functions, such as cell proliferation, the control of actin cytoskeleton
and endocytosis. We use a combination of X-ray crystallography and computational
chemistry to study the surface features that result in target specificity
across the Ras family members. This information can then be used to design
ligands that recognize a unique protein within the group. A particularly
relevant example is the design of ligands that might preferentially recognize
the oncogenic forms of Ras over the wild type, thus providing a way of
killing cancer cells without significantly harming the normal ones. A
comparative analysis of the binding site of GTPases across the Ras family
members will help elucidate key questions about how these extremely similar
proteins can have exquisite specificity for their target proteins, allowing
for very diverse biological roles.
Jeffrey
L. Thorne
Associate Professor of Statistics and Genetics
My
scientific focus is the development of statistical tools for the analysis
of DNA and protein sequences.
I have two main lines of research. One involves characterizing the relationship
between protein structure and protein evolution. The other is the estimation
of evolutionary divergence times by combining fossil information with
information from DNA and protein sequences.
Tim
Elston
Assistant Professor of Statistics and Biomathematics
My
research interests include motor proteins and transcriptional regulation.
The work on motor proteins focuses on understanding the mechanisms used
by these molecules to convert free energy, which is stored in chemical
bonds or ion gradients, into mechanical work. Gene networks are inherently
noisy, and stochastic effects can play a significant role in their dynamics.
I am interested in constructing realistic models of these regulatory systems
that take into account intrinsic noise.
