Research Abstract
As a computational genomics group, our goal is to develop machine learning methods that will provide new insights both for basic biology as well as for understanding how aberrant gene regulation plays a role in cancer, neurodegeneration, and other diseases. We seek to develop scalable, robust, rigorous computational tools for tackling important biological problems. We are particularly interested in areas involving single-cell analysis, including multi-omics assay, spatial methods, and datasets from population studies.
