Nowadays, I bring order to a swarm of cancer genomics data at Agios Pharmaceuticals and see how it factors into metabolic pathways and drug targets.
Previously, I dove into next-generation sequencing at the Broad Institute of MIT and Harvard. There I contributed to the creation of a leading system for detecting DNA variants (SNPs and short indels) as well as a generalized toolkit for analyzing massive genomic data. Some key applications of this toolkit that I have led or contributed to include: detecting de novo mutations in sequenced mother-father-child trios, detecting systematic errors in sequencing data, creating tools that decrease the negative downstream effects of these errors, and optimizing the protocols by which sequencing is targeted to specific areas of the genome.
Before joining the Broad, I completed my Ph.D. at Columbia University in the Burkhard Rost Lab. There I used genetic algorithms to select combinations of features from a complex space in order to predict protein function.
My undergraduate work included majors in Chemistry and Biochemistry at La Salle University. During that time, I had the opportunity to work extensively with custom microarray gene expression platforms and Affymetrix arrays at Rhone-Poulenc Rorer and Merck Research Labs. In this work I split my time between doing laboratory research and computational data exploration and tool development.