My group is working to understand cancer and disease signaling and metabolism, resistance to molecularly targeted drugs, and immune function from a systems viewpoint. We develop and apply genome-, proteome- and metabolome-wide detection assays, use mathematical and computational approaches to analyze our data, and follow-up our discoveries with targeted validation experiments. Data from our unbiased approaches has repeatedly led us to characterize feedback loops and synergies in cancer and immune biology. In our work we have pioneered using genome scale approaches (e.g., proteomics) side by side with targeted approaches (e.g., antibody-based) in iterative experimentation to simultaneously build a network-scale and a molecularly detailed view of biological processes (Rubbi, Science Signaling, 2011; Graham, Molecular Systems Biology, 2012). Through the UCLA Metabolomics Center we assist users with global metabolomic & proteomic profiling by mass spectrometry combined with integrated multi-omic analysis.
