A DNA language model trained on 9.3 trillion bases that can flag cancer-causing BRCA1 variants without being told about them.
Evo 2 is a DNA language model from the Arc Institute and NVIDIA built on the StripedHyena architecture, which allows a context of 1M tokens so it can read long stretches of genome at once. The 2025 bioRxiv preprint describes 7B and 40B parameter models trained on 9.3 trillion bases, and shows zero-shot variant effect prediction, including classifying BRCA1 variants as pathogenic or benign without being trained on that task, alongside generation of genomic sequences. Weights are open. For oncology the interest is in interpreting variants in cancer genes and non-coding regions. Its human regulatory prediction is weaker than specialised models such as Enformer, so it complements rather than replaces them. For a newcomer: Evo 2 learned the language of DNA well enough to spot harmful BRCA1 mutations on its own.
StripedHyena long-context sequence model over nucleotides.
Query for this technology: (TITLE:"Evo 2" OR ABSTRACT:"Evo 2" OR TITLE:"Arc Institute, NVIDIA" OR ABSTRACT:"Arc Institute, NVIDIA") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about Evo 2 (Arc Institute, NVIDIA), not a curated reading list.
Shares Autoregressive (next-token) modelling, Genomic and protein language models: Evo 2, Enformer, ESM, Variant effect prediction and the tags foundation-model, genome.
Shares the tags foundation-model, genome.
Shares the tags foundation-model, genome.
Shares the tags foundation-model, genome.
Shares Autoregressive (next-token) modelling, Genomic and protein language models: Evo 2, Enformer, ESM, Variant effect prediction.
Shares Arc Institute and the tag foundation-model.
Shares Stanford Health Care / Stanford Cancer Institute and the tag foundation-model.
Shares Stanford Health Care / Stanford Cancer Institute and the tag foundation-model.
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Arc Institute's genomic foundation model across all domains of life, with open weights.