Artificial Intelligence

The Whitehead Innovation Initiative, funded through a generous gift by Michael and Victoria Chambers, explores the power of AI tools in biological research, while establishing Whitehead Institute as a leader in applying AI tools to biological questions—often with direct implications for human health. Here are some of the achievements from the program's first year.

Artificial intelligence (AI) is part of everyday life and has innumerable uses — from summarizing a book or designing a poster, to recommending a TV show or parking your car. But how can AI be useful in biology? In this video narrated by Whitehead Institute Member Rick Young, learn how scientists are taking advantage of AI to greatly accelerate biological discoveries.

Recent symposium at Whitehead Institute convened researchers working at the intersection of AI and biology.

Henry Kilgore is a postdoc in Whitehead Institute Member Richard Young’s lab working on understanding how protein chemistry influences where in the cell proteins localize. We sat down with Henry to learn more about him and his experiences in and out of the lab.

Whitehead Institute Member Richard Young and colleagues have created a machine learning model that can predict in which cellular compartments a protein will reside, generate proteins to reside in a desired compartment, and detect disease mutations that alter cellular compartments, with implications for understanding and remedying disease.  

Andy Tseng will join the Institute on January 13, 2025 as Director of Information Technology (IT) and Digital Strategy for Whitehead Institute. In that role, he will oversee the Institute's IT operations and digital initiatives, and will help Whitehead scientists and staff leverage advanced AI technologies and innovative IT solutions to accelerate scientific discovery while ensuring data security and privacy.

Whitehead Institute has appointed Na Sun, a 2024 PhD graduate of Massachusetts Institute of Technology (MIT), as the inaugural AI Fellow within the Whitehead Fellows Program.

Researchers in Whitehead Institute Member Richard Young’s lab and colleagues at MIT show that a machine learning model can predict which subcellular compartments a drug will concentrate in based on its chemical features. This could be used to design safer and more effective drugs, and to understand how subcellular compartments govern diverse biochemical processes.