Research Projects
Dynamic Modeling of Biological Networks
We are interested in developing mathematical methods that would be useful in describing the time evolution of biological networks (e.g. prediction of future gene expression levels in a given gene network). A common challenge in modeling the dynamics of an interacting biological network is the elucidation of the optimal evolution equation of a system when the initial data is incomplete or missing. One such class of problems involves modeling a biological "sub-system" which is embedded in a larger interacting network.
Light Propagation through Complex Biological Media
Laser light offers a safe and economical way to probe into biological materials for research as well as for medical diagnostics, monitoring and treatment. It has the potential to achieve very high-resolution image data from tissues and other biological materials. Optical measurements contain information not available in data from other modalities such as X-rays and ultrasound. For example, variations in the biological sample's response to different wavelengths of light can distinguish between different bacterial species in a heterogeneous community or distinguish between malignant and benign cancer tumors.
Diffusion and Transport in Multiprotein Machines
It's becoming clear that the maintenance of both spatial and temporal chemical gradients is essential to living processes, even in bacteria [McAdams, 2003]. One example of the biological machinery that maintains such gradients is the nuclear pore complex (NPC), a exquisitely precise multiprotein machine that manages the transport of material into and out of the nucleus [Rout and Aitchison, 2001] Although the NPC is an inherently eukaryotic system, the biophysical principles by which it works are likely to underlie mechanics for molecular transport in many biological systems. The NPC consists of about 30 proteins assembled into a very large (>50 million Dalton) multiprotein machine that forms a cylindrical pore through the nuclear membrane.
Quantum Chemical Simulations of Enzyme Mechanism
Biomolecular modeling is the most established among all fields of computational biology. However, the advent of TeraFLOP-scale supercomputers opens the door to a much wider use of predictive models of biochemical processes such as enzyme mechanisms. The CCB's partnership with Lawrence Livermore National Laboratory and Sandia National Laboratory will provide students with an opportunity to get hands-on experience applying state-of-the-art molecular simulation methodologies.
