Grant from Chan Zuckerberg Initiative aids research with AI, rare diseases

DeBruine's research builds and trains generative AI to construct what he calls a patient's "cell atlas" from a small portion of genetic data, such as a blood draw or skin biopsy. With the "cell atlas," DeBruine's team can use AI to generate what whole organism cell atlases of rare disease might look like even if the rare disease was only measured in a single tissue or sample.

"Our models will also be able to generate data across species," DeBruine said. "For example, we aim to generate a portrait of what a rare disease in humans looks like, based on data collected from fish or mouse models of that disease."

DeBruine said his team has developed models with nearly 1 billion parameters and trained on more than 80 million cells, each with expression information on more than 60,000 genes.

He added the grant will support his team of four to five undergraduate students and graduate computer science students to perform full-time research. The students will develop the AI's algorithms and train these models.

"We believe our new models will harness the true power of generative AI for genomics to achieve a new level of understanding about human disease," DeBruine said. "We look forward to partnering with the single-cell data insights community at the Chan Zuckerberg Initiative to make our models accessible to every genomics researcher."