Description

This opportunity from the National Institutes of Health (NIH) supports investigator-initiated research projects that advance innovation in computational genomics, data science, statistics, and bioinformatics. The focus is on developing new analytical methodologies, early-stage tools and software, and the refinement or hardening of high-value software for the biomedical genomics community. Projects must be broadly enabling for genomics, generalizable across diseases and biological systems, and scalable to large datasets. Incremental improvements or applications of existing methods are not responsive.

Research areas of interest include, but are not limited to:

• Visualization tools for large genomic datasets
• Genetically informed causal inference methods
• Machine learning and AI for genomics (including generative AI, benchmarking, validation)
• Privacy-preserving technologies for controlled-access human genomic and clinical data
• Scalable and efficient computational methods for large-scale genomic analysis
• Integration of AI into experimental workflows
• Federated learning methodologies for distributed genomic data

Projects focused on microbial genomics, resource curation, or those not broadly generalizable are not eligible. Up to 10% of the budget may be used for experimental work to evaluate computational approaches.