James McFarland leads the Cancer Data Science group at the Broad Institute. His research focuses on computational approaches to systematically identify and understand cancer vulnerabilities. 

McFarland works closely with Francisca Vazquez to lead the Cancer Dependency Map project, a large collaborative effort aimed at building a comprehensive map of the genetic and chemical vulnerabilities across human cancers. In this role, he leads analysis efforts to quantify cancer vulnerabilities from large-scale functional genomic screens and drug-sensitivity profiling datasets, and then to relate these vulnerabilities to measurable genomic features of the cancer cells.  

The Cancer Data Science team focuses on creating and applying machine learning methods to leverage these large-scale biological datasets to predict cancer vulnerabilities, resolve their biological mechanisms, and connect them to relevant patient populations. The team also focuses on creating tools to empower the broader cancer research community to fully leverage these datasets and resources.  

Prior to joining the Broad Institute in 2016, McFarland obtained his Ph.D. in physics from Brown University. He earned a bachelor’s degree in physics from Pomona College and subsequently spent several years doing research in computational neuroscience, analyzing recordings of neural activity to determine how neurons process visual information.

Contact James McFarland via email at jmmcfarl@broadinstitute.org.