Computational cancer epigenomics
I am interested in understanding how cancers commandeer the normal regulatory machinery to create disease. As a model system, I use Ewing sarcoma, a pediatric tumor, which is a good model because it is almost always driven by a single, well-characterized mutagenic event: a chromosomal translocation leading to the fusion protein EWS-FLI1. To explore how this fusion protein re-wires the cells to proliferate uncontrollably, I am examining genome-wide epigenetic profiles of Ewing sarcoma. These types of questions lead to computational problems inherent in dealing with lots of data from different individuals, cancers, and data types.
Single-cell sequencing analysis
In the past, we have only been able to sequence populations of cells, leaving important cell-to-cell differences unexplored. New microfluidics and sequencing technology is making it possible to ask questions about single cells. Using this technology, I am interested in fundamental questions about how cells differentiate and respond to their environments at the single cell level.
Gene regulation and chromatin structure
I am interested in how cells fold their DNA to enable complex regulatory patterns. Humans are made up of many different cell-types. Though these cell-types share a single genome, they have very different phenotypes and functions, working together to enable multicellular life. The basis for these dynamics is regulatory DNA, which governs when and where different genes are expressed. I analyze data from high-throughput ChIP-seq, DNase-seq, and ATAC-seq experiments to understand how cells do this during development.