My research is in the general area of gene regulation and gene regulatory networks. We are interested in developing and applying machine learning methods to integrate high-throughput -omic datasets to gain insight into regulation and mis-regulation of gene expression. Our tools are broadly applicable to study normal processes such as development and host-symbiont interactions as well as disease processes such as cancer and diabetes, where mis-regulation of gene expression has been associated with pathological outcomes. As an Associate Research Member of the Wisconsin Diabetes Research Center, I am excited to apply my expertise to the study of diabetes related transcriptional networks.