Description

This opportunity 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 refining or hardening software of high value to the biomedical genomics community. Projects must be broadly enabling for genomics, generalizable across diseases and biological systems, and scalable to large datasets. The program is designed to catalyze advances that are widely applicable to human health and disease, rather than incremental improvements or disease-specific solutions.

Research topics 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, model validation, and benchmarking
• Privacy-preserving technologies for controlled-access human genomic and clinical data
• Methods to improve efficiency and scalability of compute-intensive genomic analyses
• Integration of AI in experimental workflows for data generation
• Federated learning methodologies for distributed genomic data and models

Applicants are encouraged to propose creative, forward-thinking research beyond these examples.

Note: Projects focused on microbial genomics, maintenance/extension of existing resources, non-generalizable methods, ontology/curation, or basic data science not developed for genomics are not responsive and will not be reviewed.