The Graham Lab focuses on using system biology approaches to understand and develop novel therapeutic approaches for cancer and other human diseases. We specialize in using mass spectrometry and other quantitative, high-content technologies to generate proteomic and metabolomic data from cancer cell lines, mouse models and human patient samples. Through integration of proteomic, metabolomic, genomic and phenotypic data, we aim to create data-driven computational models across multiple components and time scales. These models enable us to extract biological meaning from quantitative, complex data sets. Drawing on engineering, biology and statistics, we iterate between experimental and computational systems to test these predictive models. To enable discovery of new biological phenomena and translation of these systems biology models into the clinic, we are actively collaborating with chemists, physician scientists and oncologists.