We combine statistics, machine learning, tumor biology, and functional genomics for a data-driven understanding of the molecular architecture of tumor genomes and use them as an “Achilles heel” for the development of genome-inspired cancer therapies.
We are committed to training a new generation of cancer researchers from computational, experimental, and clinical backgrounds who share our core values of teaching & mentorship, collegiality & collaboration, inclusion & diversity, and mutual respect & open communication.
Our lab is part of the Computational Health Informatics Program at Boston Children's Hospital, a teaching affiliate of Harvard Medical School. This provides us with access to a unique combination of multidisciplinary collaborators, a diverse panel of clinical data, state-of-the-art computational infrastructure, and rich experimental resources.
We develop computational methods for discovering and characterizing driver mutations in coding and noncoding regions of the cancer genome.
We translate genomic drivers into targets of small-molecule therapies using experimental and functional data of cell lines and other pre-clinical models.
We collaborate with clinicians to leverage our findings for informing the design of clinical studies and improving the care and outcomes of cancer patients.