Description

This NIH opportunity supports investigator-initiated research projects that advance innovation in computational genomics and data science. The program is designed to fund development of novel analytical methodologies, computational approaches, and early-stage tools or software that are broadly applicable to genomics and human health. Projects should enable genomics research, be generalizable across diseases and biological systems, and address the challenges of scaling to larger genomic datasets. Incremental improvements, resource maintenance, or projects focused solely on a specific disease without broader applicability are not responsive.

Key areas include, but are not limited to:

• New computational, bioinformatics, statistical, or analytical approaches for genomics
• Tools for large-scale data visualization
• Genetically informed causal inference methods
• Machine learning and AI for genomics
• Privacy-preserving technologies for controlled-access data
• Scalable and efficient computation for genomics
• Integration of AI into experimental workflows
• Federated learning methodologies for distributed data

Projects must be distinct from routine application or minor modification of existing methods and should not focus on microbial genomics, resource curation, or basic data science without genomics relevance.