Federal Grant Award Summary

The University of Minnesota's Regents, through its Office of Sponsored Projects Administration, received a $333,290 Project Grant from the National Institute of General Medical Sciences under the Biomedical Research and Research Training program (CFDA 93.859) effective March 1, 2026, through February 28, 2031. This award supports the development of a comprehensive analytical framework for integrating high-throughput biomedical data across multiple sources, dimensions, and patient cohorts. The research team will create novel statistical methodology and computational tools to simultaneously identify covariate-driven effects and underlying structured variation in complex multi-dimensional datasets, with applications to neurodegenerative disorders, pulmonary disorders, early-life nutrition, and related biomedical domains.

The deliverables under this grant include a flexible bidimensional regression and factorization framework capable of decomposing covariate effects and low-rank structures, development of Bayesian inference algorithms for efficient posterior sampling, missing data imputation techniques, sample cohort classification methods, and longitudinal progression tracking tools. These methodological advances will be complemented by applied research demonstrating the framework's utility across diverse biomedical areas. The award builds on the principal investigator's established track record of developing impactful statistical methods and widely-adopted software for data integration in high-throughput biomedical research settings.