Ragon Institute

Lab Overview

Aging is the greatest risk factor for a broad range of chronic diseases. We have a long-standing interest in understanding the complex biology of aging from the level of the fundamental biological unit (the cell) to the level of the whole system (the organism). Such an understanding can be leveraged to discover and engineer interventions for broadly improving human health and staving off disease. To that end, we develop computational and machine learning tools to (1) measure biological aging from cell to organism, (2) predict and simulate the effects of interventions, including genetic and immune perturbations, on cells and tissues, and (3) design new interventions against aging and optimize their parameters for improved efficacy. We integrate computational frameworks for model building with experimental approaches for biological data generation and model validation.