“I don’t like to be alarmist,” said Katherine Keyes, a professor of epidemiology at Columbia University. “But I think at this point, it’s pretty alarming.”
“Biology is being transformed into something that is a predictive science,” said Raul Rabadan, one of the authors of a paper reporting the work Wednesday in the journal Nature.
Marianthi-Anna Kioumourtzoglou, a professor of environmental health sciences at Columbia University, said that while the lower-cost sensors were not perfect, they could provide valuable information.
In the same way that ChatGPT understands human language, a new AI model developed by Columbia computational biologists captures the language of cells to accurately predict their activities.
Editor's Note: Jason Liebowitz, author of this article, is an assistant professor of medicine in the Division of Rheumatology at the Columbia University Vagelos College of Physicians and Surgeons.
By generating movies of individual molecules performing actions that make our bodies tick, Columbia researchers have a deeper understanding of a process important in cancer and other diseases.
A new study shows that some of our cells favor genes of one parent or the other and can explain a longstanding mystery of why some people with disease-causing genes experience no symptoms.
Editor's Note: Catherine Monk, interviewed for this PBS Newshour segment, is chief of the Division of Women's Mental Health at the Columbia University Vagelos College of Physicians and Surgeons.
