Bridge2AI recommendations for AI-ready genomic data.

Authors

Matthew Cannon, Wesley Goar, In-Hee Lee, James Stevenson, Amy Heiser, Nathan C Sheffield, James Eddy, Monica Munoz-Torres, Sek Won Kong, Alex H Wagner

Published in

Bioinformatics advances. Volume 6. Issue 1. Pages vbag305. Epub Oct 25, 2026.

Abstract

Rapid advancements in technology have led to an increased use of artificial intelligence (AI) technologies in medicine and bioinformatics research. In anticipation of this, the National Institutes of Health (NIH) assembled the Bridge to Artificial Intelligence (Bridge2AI) consortium to coordinate development of "AI-ready" datasets that can be leveraged by AI models to address grand challenges in human health and disease. The widespread availability of genome sequencing technologies for biomedical research presents a key data type for informing AI models, necessitating that genomics data sets are "AI-ready." To this end, the Genomic Information Standards Team (GIST) of the Bridge2AI Standards Working Group has documented a set of recommendations for maintaining AI-ready genomics datasets. In this report, we describe recommendations for the collection, storage, identification, and proper use of genomics datasets to enable them to be considered "AI-ready" and thus drive new insights in medicine through AI and machine learning applications.

PMID:
42928829
Bibliographic data and abstract were imported from PubMed on 26 Oct 2026.

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