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Etowah Adams

@etowah0.bsky.social

106 followers 228 following 31 posts

enjoying and bemoaning biology. phd student @columbia prev. @harvardmed @ginkgo @yale

Etowah Adams @etowah0.bsky.social · 21/08/2026

OpenBind intends to collect 10,000s of protein-ligand structures & affinities. To prioritize what we collect next, we need cofolding models trained on the latest data. Today we're releasing OpenBind-0 and 717 new ligand-bound structures.

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Reciprocal Space Station @rs-station.bsky.social · 21/07/2026

1/ We're excited to announce that @rs-station.bsky.social is joining the Open Molecular Software Foundation @omsf.io!

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Etowah Adams @etowah0.bsky.social · 13/03/2026

Huge resource for the community. Turning compute into data to train models to turn more compute into data...the cycle must go on bsky.app/profile/moal...

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Reposted by Etowah Adams

Mohammed AlQuraishi @moalquraishi.bsky.social · 13/03/2026

New OpenFold3 preview out! (OF3p2) It closes the gap to AlphaFold3 for most modalities. Most critically, we're releasing everything, including training sets & configs, making OF3p2 the only current AF3-based model that is functionally trainable & reproducible from scratch🧵1/9

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Tristan Bepler @tbepler.bsky.social · 11/02/2025

Excited to share PoET-2, our next breakthrough in protein language modeling. It represents a fundamental shift in how AI learns from evolutionary sequences. 🧵 1/13

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Mohammed AlQuraishi @moalquraishi.bsky.social · 10/02/2025

It's long seemed that molecular biology is a natural home for ML interpretability research, given the maturity of human-constructed models of biological mechanisms—permitting direct comparison with their ML-derived counterparts—unlike vision and NLP. Our first foray below👇.

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Reposted by Etowah Adams

Diego del Alamo @delalamo.xyz · 10/02/2025

This might be the best paper on applying sparse autoencoders to protein language models. The authors identify how neural networks trained on amino acid sequences "discover" different features, some specific to individual protein families, other for substructures www.biorxiv.org/content/10.1...

A range of features identified from sparse autoencoders trained on different layers on ESM2-650M

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Etowah Adams @etowah0.bsky.social · 10/02/2025

Can we learn protein biology from a language model? In new work led by @liambai.bsky.social and me, we explore how sparse autoencoders can help us understand biology—going from mechanistic interpretability to mechanistic biology.

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