The Stewart Computational Group is driven by two goals: (1) building foundational datasets, models, and algorithms useful to other researchers and (2) finding patterns in large datasets for establishing targets for further wet-lab analysis. To these ends, we develop and utilize algorithms for the analysis of large biomedical omics datasets, including genomics, transcriptomics, epigenomics, multi-omics, and bibliomics (biomedical text). Collaboration is at the heart of what we do and through the variety of projects we collaborate with researchers from the Morgridge Institute for Research, the University of Wisconsin, and other institutions around the world.
See our GitHub for some of our publicly available code.
