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by @danabra.mov
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by @danabra.mov
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by @jimpick.com
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by @atsui.org
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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)
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www.biorxiv.org
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...
Rewriting protein alphabets with language models
Lorenzo Pantolini