EnhancAR: Use evolution and deep learning to design enhancers with desired expression profiles!

Had a lot of fun working with Andrew Duncan, Micaela Consens @alexijie.bsky.social @lcrawford.bsky.social Jennifer Mitchell and Alan Moses!

www.biorxiv.org/content/10.6...

Check out how we exploit observations of homology from evolution to design enhancers, even when we don't have prior knowledge or ability to specify function!

Five years ago, we released FLIP. The core question was: can ML models for protein fitness prediction generalize in the ways that actually matter for protein engineering, i.e. low data, extrapolation to more mutations, out-of-distribution sequences?

We made FLIP2, a protein fitness benchmark spanning seven new datasets, including enzymes, protein-protein interactions, and light-sensitive proteins, as well as splits that measure generalization relevant to real-world protein engineering campaigns.

Come do a PhD internship with me!

Was incredible to work with Arushi during her summer internship - check out her preprint showing that single cell representation learning methods for microscopy can be confounded by cells in the background of their inputs!

Read our preprint that demonstrates a growing bias in medical imaging datasets against pediatrics, and how it impacts downstream AI development!

Props to our first author @stanhua.bsky.social, who among many other feats, filtered hundreds of datasets/papers to establish this trend.

At NeurIPS and interested in talking about BioML? Catch me at the Microsoft booth in the expo hall between 2:00-2:30p and 3:30-4:30p today!