Award
National Institute of General Medical Sciences 5R35GM150537-03
Interpretable Bayesian Non-linear statistical learning models for multi-omics data integration
Recipient
University of Minnesota
Award Amount
$374,672.00
Ceiling
$374,672.00
Awarded
July 30, 2025
Identifier
5R35GM150537-03
Award for developing Bayesian statistical learning models for multi-omics data integration to identify disease biomarkers and molecular subtypes, funded by NIGMS.
Description
The project involves developing and applying Bayesian statistical learning methods for multi-omics data integration. The award is funded by the National Institute of General Medical Sciences (NIGMS). The project aims to identify predictive pathways, molecular subtypes, and biomarkers for complex diseases. The project will utilize datasets such as The Cancer Genome Atlas, dbGAP, and Genotype-Tissue Expression. Software developed will be robust, computationally efficient, and user-friendly.