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A wider field of view to predict expression

Nature Methods volume 18, pages 1155–1156 (2021)Cite this article

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A gene sequence-to-expression machine learning model achieves improved accuracy by incorporating information about potential long-range interactions.

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Fig. 1: Prediction of gene expression by Enformer.

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Acknowledgements

This work was supported by NIH award U01 HG009395.

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Authors and Affiliations

  1. Department of Genome Sciences, University of Washington, Seattle, WA, USA

    Yang Young Lu & William Stafford Noble

  2. Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA

    William Stafford Noble

Authors
  1. Yang Young Lu
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  2. William Stafford Noble
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Correspondence to William Stafford Noble.

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The authors declare no competing interests.

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Lu, Y.Y., Noble, W.S. A wider field of view to predict expression. Nat Methods 18, 1155–1156 (2021). https://doi.org/10.1038/s41592-021-01259-4

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