Research in our lab focuses on developing data-mining algorithms and informatics solutions for problems in biology and medicine. Current projects are focused on two closely related areas – (A) mammalian gene regulation at isoform-level, and (B) isoform-level gene regulatory networks in brain development and brain tumors. The overarching goal of our lab is to translate data from high dimensional (-omic) platforms (e.g., NextGen sequencing) to derive experimentally interpretable and testable discovery models towards genomics-based clinical decision support systems for personalized cancer therapy. We are developing clinically useful diagnostic tools for identification of subsets of brain tumor patients who may benefit from therapeutic intervention and guide the understanding of drug activity in patient tumors. Towards these goals, we apply a combination of state-of-the-art statistically rigorous data-mining methods and NextGen sequencing based experimental procedures in a systems biology setting.