Hello everyone,

Join us next *Wednesday, May 6th at 1 pm ET* for a compelling look at how MaizeGDB is transforming maize research with AI-ready data infrastructure. Discover how cutting-edge DNA and protein language models, precomputed features, and interactive tools are unlocking faster gene discovery and smarter crop improvement. See how standardized, accessible genomics data is paving the way for the next generation of agricultural innovation.

As part of the AgBioData webinar series, *Olivia Haley*, a USDA-ARS Postdoctoral Research Fellow at the Oak Ridge Institute for Science and Education, will present the talk titled: “*Delivering AI-Ready Genomics with MaizeGDB*”.

The zoom link and abstract are below. We hope you can join us!

Best,

Marcela

-- Wednesday, May 6th, 1PM ET | 1P ET | 12P CT | 11A MT | 10A PT | Find your local time *here* https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+May+2026+Webinar+-+Olivia+Haley&iso=20260506T12&p1=405&ah=1 .

Join Zoom Meeting https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09 Meeting ID: 820 3835 6125 Passcode: 160683 --

Speaker: *Olivia Haley, *USDA-ARS Postdoctoral Research Fellow at the Oak Ridge Institute for Science and Education

Title: Delivering AI-Ready Genomics with MaizeGDB

Abstract: The integration of Artificial Intelligence (AI) into computational biology is changing biological research, particularly in agriculture, where large and complex datasets offer opportunities for discovery and crop improvement. Maize (Zea mays L.), a globally critical crop with extensive genomic, genetic, proteomic, and functional resources, stands to benefit from AI integration. The Maize Genetics and Genomics Database (MaizeGDB) is proactively building an AI-ready infrastructure by standardizing datasets, pre-computing complex features, developing novel interactive tools, and providing reproducible workflows. This paper details MaizeGDB's strategic initiatives to create a foundation of AI-ready data in standardized formats and generate precomputed embeddings from cutting-edge DNA and protein language models. We introduce new functionalities, including zero-shot variant effect scoring derived from biological language models (protein and DNA) and genome browser tracks for visualizing nucleotide conservation (conveying potential functional significance). Furthermore, we provide custom dataset assembly resources and reproducible workflows via GitHub. By providing access to and organization of maize data, MaizeGDB enables the maize research and breeding community to leverage AI for the accelerated discovery of gene function, variant interpretation, and the development of improved maize varieties.