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Variant effect prediction

Advancing variant effect prediction using protein language models

Nature Genetics volume 55, pages 1426–1427 (2023)Cite this article

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A novel pipeline that expands the utility of the protein language model ESM1b has provided variant effect predictions for more than 40,000 protein isoforms. This strategy outperformed several state-of-the-art methods over multiple benchmarks.

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Fig. 1: The improvement in missense VEP performance over time.

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Authors and Affiliations

  1. MRC Human Genetics Unit, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK

    Benjamin J. Livesey & Joseph A. Marsh

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  1. Benjamin J. Livesey
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  2. Joseph A. Marsh
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Correspondence to Joseph A. Marsh.

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The authors declare no competing interests.

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Livesey, B.J., Marsh, J.A. Advancing variant effect prediction using protein language models. Nat Genet 55, 1426–1427 (2023). https://doi.org/10.1038/s41588-023-01470-3

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