Proteomics and bioinformatics

My group studies the large-scale organization of proteins, essentially trying to reconstruct the ‘wiring diagrams’ of cells by learning how all of the proteins encoded by a genome are associated into functional pathways, systems, and networks. We are interested both in discovering the functions of the proteins as well as in learning the underlying organizational principles of the networks. The work is evenly split between computational and experimental approaches, with the latter tending to be high-throughput functional genomics and proteomics approaches for studying thousands of genes/proteins in parallel.

Bioinformatics for discovering protein function

We've discovered a number of features of genomes that allow us to predict functions for proteins that have never been experimentally characterized. Using these techniques and information from over 30 fully sequenced genomes, we were able to calculate the first genome-wide predictions of protein function, finding very preliminary function for over half the 2,500 uncharacterized genes of yeast. Now, with hundreds of genomes in hand, we're extending these techniques, as well as asking basic questions about the evolution of protein interactions and the evolution of genomes.

Proteomics: High-throughput protein expression and interaction profiling

From work of ours and others, it is apparent that proteins in the cell participate in extended protein interaction networks involving thousands of proteins. We are interested in mapping these networks, measuring their dynamics, and using the networks to predict cell behavior and protein function. In the near term, we are developing mass spectrometry methods to measure absolute protein abundances and high-throughput microscopy methods to measure protein sub-cellular locations and activities, both of which allow us to test and extend the network models. In the long term, we would like to build a catalog of protein, mRNA and metabolite expression from cells grown under many different conditions, forming a quantitative picture of these molecular events inside cells. We expect that data of these sorts will put us on the road to developing predictive, rather than descriptive, theories of biology.