Introducing Quine: An AI research system designed for the complexity of biology

What happened

That work has produced foundational methods, new science, and technology that reached the clinic, from rare and infectious disease diagnosis to cancer biomarker detection. For more than two decades, Microsoft Research has worked at the intersection of computation and biology.

Genes influence proteins; proteins interact within cells; cells organize into tissues; and experiments continually reshape what scientists know and what they choose to ask next. Making progress on the hardest biological questions therefore requires more than increasingly capable models of individual datasets or tasks.

It requires systems that can connect knowledge across scale and modalities, reason about experiments and evidence, and participate in the iterative process through which science advances. Quine brings together a world model of biology with a harness that connects scientific tools, literature, the wet lab, and the researchers using them. Nature cannot be rushed, nor can it be derived from first principles.

Key facts

• Making progress on the hardest biological questions therefore — requires: more than increasingly capable models of individual datasets or tasks