Casey Greene’s lab at the University of Pennsylvania is dedicated to developing computational tools that biologists use to gain insights from other labs’ data as easily as from their own. More than 2 billion dollars’ worth of publicly funded genomics data are freely downloadable. These data represent a rich and underused resource, but they are hard to use because the data are comprised of many different experiments. Standard algorithms struggle with these “messy” datasets. Casey’s lab develops computational techniques that are robust enough to analyze and interpret this public resource. These algorithms have applications across many disease areas and, perhaps most importantly, to questions of basic biology.
Casey’s devotion to the analysis of publicly available data doesn’t stop in the lab. In 2016, Casey established the “Research Parasite Awards” after an editorial in the New England Journal of Medicine deemed scientists who analyze other scientists’ data “research parasites.” These honors, accompanied by a cash prize, are awarded to scientists who rigorously reanalyze other people’s data to learn something new.
Casey earned his Ph.D. for his study of gene-gene interactions in the field of computational genetics from Dartmouth College in 2009 and moved to the Lewis-Sigler Institute of Integrative Genomics at Princeton University where he worked as a postdoctoral fellow from 2009-2012. He started a lab in the Department of Genetics in the Geisel School of Medicine at Dartmouth before moving to Penn in 2015 where he is an Assistant Professor in the Department of Systems Pharmacology and Translational Therapeutics.