Understanding development arising from stem cells using molecular profiles like gene expression microarray, genome wide methylation marks, RNASeq, and histone mark dynamics is currently our state of the art. All of these approaches measure a single dimension of molecular event. How can this be translated to how the cell is functioning at the developmental time point, and how can this be compared between experiments that are using different platforms, cell types, and whatever else?
Harvard School of Public Health Dana-Farber Cancer Institute
Our research group focuses on methods spanning the laboratory to the laptop that are designed to use genomic and computational approaches to reveal the underlying biology. In particular, we have been looking at patterns of gene expression in cancer with the goal of elucidating the networks and pathways that are fundamental in the development and progression of the disease.