Brian’s research is in computational biology, applying advanced statistical, mathematical, and algorithmic methods to discover and understand new biology. In particular, post–transcriptional RNA-based gene regulation mechanisms genome-wide. His work has led to the discovery of new regulatory mechanisms in liver metabolism and immunity. His areas of theoretical focus include; comparative genomics, hidden state probabilistic models, machine learning and deep neural networks, functional data analytic models, and algorithmic graph theory.