Thomas Graeber is faculty in the Department of Molecular and Medical Pharmacology and a member of the Crump Institute for Molecular Imaging at UCLA, and is a Melanoma Research Alliance Established Investigator and an American Cancer Society Research Scholar. His background includes physics, cancer biology, signal transduction, metabolism, computational biology, proteomics, and metabolomics. His work builds experimental and computational approaches to studying cancer signaling and metabolism from a systems perspective. His work in cancer biology started with the discovery that hypoxia, a common feature of solid tumors, induces p53 protein levels, and that p53 deficient cells are less prone to undergo apoptosis in low oxygen conditions, conferring a survival advantage. These findings led to a model of hypoxia as a physiological selective force against apoptosis-competent cells in developing tumors, thus explaining the previously unaccounted for high frequency of p53 mutations in cancer. In computational biology, he developed an algorithm to identify potential autocrine signaling loops in cancer using gene expression microarray data. The algorithm integrates biological data (in this case, cognate ligand-receptor partners) into the analysis of raw gene expression data, and a number of leads from this method have been verified to play critical roles in cell signaling. His work in integrated signaling and metabolic networks has repeatedly pointed to the importance of negative and positive feedback loops in cancer phenotypes, and he is investigating approaches to therapeutically disrupting cancer-specific reliance on these feedback mechanisms.