Protein Set Transformer: a protein-based genome language model to power high-diversity viromics
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Abstract
Exponential increases in microbial and viral genomic data demand transformational advances in scalable, generalizable frameworks for their interpretation. Standard homology-based functional analyses are hindered by the rapid divergence of microbial and especially viral genomes and proteins that significantly decreases the volume of usable data. Here, we present Protein Set Transformer (PST), a protein-based genome language model that models genomes as sets of proteins without considering sparsely available functional labels. Trained on >100k viruses, PST outperforms other homology- and language model-based approaches for relating viral genomes based on shared protein content. Further, PST demonstrates protein structural and functional awareness by clustering capsid-fold-containing proteins with known capsid proteins and uniquely clustering late gene proteins within related viruses. Our data establish PST as a valuable method for diverse viral genomics, ecology, and evolutionary applications. We posit that the PST framework can be a foundation model for microbial genomics when trained on suitable data.
Article activity feed
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Excited for our new paper on a genome language model for viruses in @natcomms.nature.com: "Protein Set Transformer: a protein-based genome language model to power high-diversity viromics"! Led by PhD student Cody Martin in collaboration with @anthonygitter.bsky.social doi.org/10.1038/s414...
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Protein Set Transformer: a protein-based genome language model to power high-diversity viromics | Nature Communications https://www.nature.com/articles/s41467-025-66049-4
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Protein Set Transformer: A protein-based genome language model to power high diversity viromics [updated] Models viral genomes as prot. sets, bypassing functional labels for analysis of diverse viral seqs.
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Protein Set Transformer: A protein-based genome language model to power high diversity viromics www.biorxiv.org/content/10.1... #VGEB24
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There has been growing caution around biological foundation models due to532potential biosecurity threats such as generating novel pathogenic viruses or guiding533gain-of-function viral mutations
It might be good to mention this rationale/justification and thought process earlier in the preprint so people understand why the code isn't available right now.
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Figure 6.
Not sure if done on purpose, but this figure shows up really light and it's difficult to see some details
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Abstract
When the code is available, it would be good to link it in the abstract since this is a cool tool people will want to use!
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Excited to share our latest work on development of PST, a genome language model for viruses and phage. We believe PST can be a foundation model for viromics and enable broad viral ecology and bioengineering applications. Study led by PhD student Cody Martin. www.biorxiv.org/content/10.1...
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Protein Set Transformer: A protein-based genome language model to power high diversity viromics https://www.biorxiv.org/content/10.1101/2024.07.26.605391v1
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Protein Set Transformer: A protein-based genome language model to power high diversity viromics https://www.biorxiv.org/content/10.1101/2024.07.26.605391v1
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