Robert F. Murphy

Dr. Murphy’s group does both experimental and computational cell biology, with a particular emphasis on developing fully-automated methods to understand the subcellular locations of proteins and how they change during development or disease (location proteomics). They use machine learning methods to compare, classify and cluster spatiotemporal patterns in microscope images and construct generative models directly from images to capture the essence of each subcellular pattern as well as the variation in pattern from cell to cell. The goal is to identify all “subcellular location families”, how they change (especially during oncogenesis) and to provide generative models for each family that can be incorporated into systems biology simulations. They are particularly interested in active learning approaches to create closed loop systems of interpretation, modeling, experiment planning and automated data acquisition, enabling automated scientific discovery.