We develop computational methods for the analysis and integration of molecular sequence, structure, and expression data. Our aim is to understand organismal biology by interpreting the information encoded in complete genomes. This work is presently focused on the areas of structural and functional genomics.
Structural genomics projects attempt to provide an experimental structure or a good theoretical model for every tractable protein in all completed genomes. Our work involves organizing proteins into families according to homology; classifying proteins and RNA according to structure; predicting structure from homology and constructing atomic coordinate models; providing information resources for structural genomics; developing methods for selection of proteins for experimental characterization; and analyzing solved structures to detect homology and functional information.
We study computational functional genomics by creating algorithms using molecular sequence, structure, phylogeny, and expression information to infer the functions of genes. This work includes the use of gene genealogies to trace gene histories and functional divergences; reverse-genomics comparison of multiple complete genomes to locate genes associated with characterized cellular or biochemical functions; creation of databases of genomic information; and continued refinement of sequence comparison methods. We also combine sequence comparison with expression and other experimental data to improve molecular and cellular functional characterization.
For more information, see the Brenner Group Homepage.