Rok Breznikar
@rokbreznikar.bsky.social
Reposted by Rok Breznikar
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)
Pre-print: www.biorxiv.org/content/10.1...
🧵👇(1/n)
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...
www.biorxiv.org
December 1, 2025 at 10:28 AM
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)
Pre-print: www.biorxiv.org/content/10.1...
🧵👇(1/n)
Reposted by Rok Breznikar
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)
www.biorxiv.org/content/10.1...
🧵👇 (1/n)
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...
www.biorxiv.org
February 8, 2025 at 10:02 AM
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)
www.biorxiv.org/content/10.1...
🧵👇 (1/n)