Room 262B, Rosen Building, South Lake Union
A fundamental issue facing modern biology is the development of methods and tools to convert genomics and function genomics data into mechanistic understanding. Genome sequences and computational methods have provided us with tools to identify and annotate genes and other functional sequences with varying degrees of accuracy. Annotated sequence information in turn enables tools such as RNA-Seq, microarrays, 2-D gels, protein mass spectrometry and yeast 2-hybrids to measure RNA and protein levels and physical interactions on genome-wide or near genome-wide scales. Genome information has also enable high-throughput genetic mapping technologies that allow one to rapidly trace a given phenotype or trait to specific genetic regions. However, in most cases there is still a major gap between the collection of large-scale genomic/genetic data and the inference of biological mechanism for a particular state, disease, or clinical outcome. This gap between large-scale data collection and biological understanding has become extremely apparent in the last many years during which an increasing number of large-scale genomics studies have been published which made little contribution to new biological understanding. One focus of my research efforts is on the creation of tools to connect functional data to biological meaning and the application of these tools to wide variety of biological problems.
In addition, we have a large amount of effort devoted to comparative genomics of clinical isolates of bacteria from humans. In particular, we focus on Aggregatibacter actinomycetemcomitans (Aa) and Propionibacterium acnes (Pa). Aa is associated with periodontitus while Pa is associated with acnes and infections of prosthetics. Our primary goal is to use comparative genomics methods to identify virulence factors in these organisms.
Copyright © 2003-2014 Molecular & Cellular Biology Program, University of Washington
Fred Hutch | University of Washington
Institute for Systems Biology (ISB)| Center for Infectious Disease Research