Pablo Tamayo BS, PhD

During the last two decades Pablo Tamayo has worked on the study of oncogenes, cancer pathways and targets, molecular signatures of oncogene activation and dependence, treatment outcome, disease subtypes, gene dependency and drug response. Over the last 5 years he has also worked in the functional characterization of cancer genomes and oncogenic states, including RNAi and CRISPR genetic dependencies.

These methods include, e.g., the use of matrix decomposition for pattern discovery, the feature selection PARIS algorithm, single-sample Gene Set Enrichment Analysis (GSEA), the REVEALER algorithm to identify groups of genomic alterations that together correlate with a given activation, gene dependency, or drug response profile, DisCoVER, a method to find drugs or perturbagens that associate with a given oncogenic signature, and Onco-GPS, a data-driven analysis framework to identify oncogenic cellular states. He is currently Professor in the UCSD School of Medicine and co-director of UCSD Moores Cancer Center Genomics and Computational Biology