Sushmita Roy named 2018 Vilas Associate
Long-range regulatory interactions occur between a gene and a regulatory sequence element hundreds of kilobases away. Such interactions are important drivers of cell type-specific gene expression and can play critical roles in the interpretation of regulatory variants in normal and disease processes including cancer, diabetes and obesity. However, these interactions are largely unknown in the majority of cell types and species. The overall goal of this project is to develop novel computational methods, based on statistical machine learning, to predict long-range regulatory interactions in new cell types and species. Predicted interactions in diverse cell types and species will enable us to gain novel insights into dynamics of long-range regulation in different developmental and evolutionary contexts and enable us to link regulatory variants to genes and complex traits.