Understanding G-protein subunit association (Green).
Groups affiliated with the department are involved in active research in Computational Biology at all levels. Major initiatives in Structural Biology are combined with an active presence in the emerging field of Systems Biology. In addition, computational applications are being developed and deployed to process and explain experimental data ranging from microscopy to global gene-expression profiles.
Experimental techniques such as X-ray crystallography and NMR spectroscopy can give an atomic-detail view of the structures of biological molecules and molecular complexes. Computational methods allow for the exploration of energetic and dynamic effects based on this structural information. Active research programs include molecular dynamic studies of protein folding, virtual screening and drug design, and the analysis and design of protein complexes. (Deng, Green, Rizzo, Simmerling, Wang)
Traditional genetic, molecular biological, and biochemical methods have been central to the development of our understanding of biological systems to date. These reductionist approaches have focussed on building detailed models for the action of individual components (genes, gene products, or metabolites). It is increasingly clear, however, that many biological repsonses can only be understood as the emergent properties of a system of interacting components. The study of these networks of interactions in an integrated manner has been termed Systems Biology. On-going research involves a number of systems: understanding gene-regulatory networks in fly development, elucidating the role of specificity in eukaryotic signal transduction pathways, and the effect of noise on biochemical reaction networks. (Green, Reinitz, Wang)
Statistical modeling of genetic networks (Zhu).
Modern biology necessarily involves dealing with vast quantities of data: the sequences of multiple genomes, the results of high-throughput experiments, and even simply the literature of more than five decades of molecular biology and biochemistry. Extracting knowledge from this raw information is a major problem, and the solutions are necessarily computational. Work is ongoing on methods for the analysis of genome sequences and of high-throughput transciptional activation experiments, as well as on data mining in protein-interaction databases. (Green, Rest, Skiena, Wang, Zhu)
Another experimental area with a major compuational aspect is that of imaging. Electron and light microscopy, MRI, and PET all can be used to give 3-dimensional structural information about biological systems ranging from macromolecular complex, through individual cell, to whole tissues. Computational methods are necessary for storing and processing large data sets, for refining raw experimental output, and for extracting meaningful information from the data. A number of groups at Stony Brook are involved in problems of microscopy, while MRI and PET are a major compoment of biomedical studies at nearby Brookhaven National Laboratory. (Lindquist, Reinitz, Zhu)
Computational methods can play a key role in understanding the mechanisms of evolution. Simulations can used to gain insight into how selective pressure and natural genetic drift together lead to variation in populations. Compuational approaches are additionally essential to elucidating evolutionary trends from large data sets taken from multiple species. (Rest, True)
Combining rigorous mathematical and physical theory with simplified models of biological systems can give important insights into fundamental principles. Theoretical approaches can also be be combined with high-level computational methods to provide quantitative models of complex, dynamic systems. Work on understanding protein folding and dynamics, as well as studies of enyzmatic catalysis, are key areas of interest. (Fortmann, Wang)
This page is maintained by David F. Green <dfgreen@ams.sunysb.edu>. Last updated: Wed Jan 20 14:39:31 2010.Copyright © 2006 Department of Applied Math & Statistics - Stony Brook University. All rights reserved.