What can computational biology teach us about cancer? In this capstone experience for the Genomics, Proteomics, and Bioinformatics program, computational analysis and wet-lab investigations will inform each other, as students majoring in biology, chemistry, computer science, mathematics/statistics, and physics contribute their own expertise to explore how ever-growing gene and protein data-sets can provide key insights into human disease. In this course, we will take advantage of one well-studied system, the highly conserved Ras-related family of proteins, which play a central role in numerous fundamental processes within the cell. The course will integrate bioinformatics and molecular biology, using database searching, alignments and pattern matching, and recombinant DNA techniques to reconstruct the evolution of the RAS gene family by focusing on the gene duplication events and gene rearrangements that have occurred over the course of eukaryotic speciation. By utilizing high through-put approaches to investigate genes involved in various signal transduction pathways, students will identify pathways that are aberrantly activated in mammalian cell lines carrying a mutant, constantly active Ras protein. This functional genomic strategy will be coupled with microscopic examination of tissue sections from a variety of human colon tumors, using phosphorylation-state specific antisera, to test our hypotheses. Proteomic analysis will introduce the students to de novo structural prediction and threading algorithms, as well as data-mining approaches to identify specific amino acids involved in protein-protein contacts. Flow cytometry and mass spectrometry will be used to study networks of interacting proteins in normal colon and colon tumor tissue.