Naedine Hazell, Yale School of Medicine; Bridging Biology and AI: Yale and Google's Collaborative Breakthrough in Single-Cell RNA Analysis
"Google and Yale researchers have developed a more “advanced and capable” AI model for analyzing single-cell RNA data using large language models that is expected to “lead to new insights and potential biological discoveries.”
“This announcement marks a milestone for AI in science,” Google announced.
On social media and in comments, scientists and developers applauded the model—which Google released Oct. 15—as the much-needed bridge to make single-cell data accessible, or interpretable, by AI.
Many scientists, including cancer researchers focusing on improving the outcomes of immunotherapies, have homed in on single-cell data to understand the mechanisms of disease that either protect, or thwart, its growth. But their efforts have been slowed by the size and complexity of data...
“Just as AlphaFold transformed how we think about proteins, we’re now approaching that moment for cellular biology. We can finally begin to simulate how real human cells behave—in context, in silico," van Dijk explained, following Google's model release. "This is where AI stops being just an analysis tool and starts becoming a model system for biology itself.”
An example of discoveries that could be revealed using this large-scale model with improved predictive power was tested by Yale and Google researchers prior to the release of the model. The findings will be shared in an forthcoming paper.
On Wednesday, the scaled-up model, Cell2Sentence-Scale 27B was released. The blog post concluded: “The open model and its resources are available today for the research community. We invite you to explore these tools, build on our work and help us continue to translate the language of life.”"
