Ian Hay 🧬

What Biology Can Learn from Physics 🚀 World War II shifted physics from a field of brilliant individuals to one of well-managed teams. CERN, LIGO, and the JWST all cost >$1 billion. Biology has had a few "moonshots," but not nearly as many. Why not? Read: readcodon.com/p/biology-phys… *** There are probably a few reasons. First, biology research is inherently broad. A zoologist, ecologist, and protein engineer all call themselves “biologists,” but rarely attend the same conferences. Biological discoveries are also made organically, with thousands of teams chipping away at problems. And it's opaque; researchers don’t share their results until a paper is published. These quirks make it difficult to coordinate on large problems.  The foundation of physics has been built over several centuries, thanks to a constant back-and-forth dialogue between theory and experiment. Progress in biology will similarly accelerate once the field builds predictive models that can accurately anticipate the outcome of experiments before they have taken place. AlphaFold2, a model that predicts protein structures, was a great start. But now, biologists should work to build predictive models at more scales: from molecules, to whole cells, to the behavior of cells at the macroscale. This is what @Align_Bio and others are doing. But it will require large-scale funding and coordination amongst biologists. The last century of biology looked like an organic and exploratory process, with many small groups discovering and rediscovering curiosities. But the next century may resemble a coordinated, whole-field effort to divide biology into a series of prediction tasks and then solve those tasks, one-by-one. This piece was written with @erika_alden_d.