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Rok Breznikar

@rokbreznikar.bsky.social
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Reposted by Rok Breznikar
Janani Durairaj (Jay) @ninjani.bsky.social · 28/08/2026
Some exciting news: I'm joining the University of Lausanne @unil.bsky.social @dbc-unil.bsky.social as an Assistant Professor next month 🎉 My group will work on context-aware deep learning for protein structure, interaction & design. Postdoc and PhD openings coming soon - keep an eye out!
compare, predict, design
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Reposted by Rok Breznikar
Lorenzo Pantolini @lorenzopantolini.bsky.social · 01/12/2025
Fresh from bioRxiv our latest work introducing The Embedded Alphabet (TEA), a powerful new representation for protein sequences obtained by discretising ESM2 embeddings into 20 characters. Pre-print: www.biorxiv.org/content/10.1... 🧵👇(1/n)
biorxiv.org
Rewriting protein alphabets with language models
Detecting remote homology with speed and sensitivity is crucial for tasks like function annotation and structure prediction. We introduce a novel approach using contrastive learning to convert protein...
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Reposted by Rok Breznikar
Peter Škrinjar @peterskrinjar.bsky.social · 08/02/2025
Excited to share our latest preprint evaluating AlphaFold3, Boltz-1, Chai-1 and Protenix for predicting protein-ligand interactions, featuring our newly introduced benchmark dataset 🌹Runs N’ Poses🌹! www.biorxiv.org/content/10.1... 🧵👇 (1/n)
biorxiv.org
Have protein-ligand co-folding methods moved beyond memorisation?
Deep learning has driven major breakthroughs in protein structure prediction, however the next critical advance is accurately predicting how proteins interact with other molecules, especially small mo...
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