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Author Correction: DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires

Author

Listed:
  • John-William Sidhom

    (Johns Hopkins University School of Medicine
    Johns Hopkins University School of Medicine
    Johns Hopkins University School of Medicine)

  • H. Benjamin Larman

    (Johns Hopkins University School of Medicine
    Johns Hopkins University School of Medicine)

  • Drew M. Pardoll

    (Johns Hopkins University School of Medicine
    Johns Hopkins University School of Medicine)

  • Alexander S. Baras

    (Johns Hopkins University School of Medicine
    Johns Hopkins University School of Medicine
    Johns Hopkins University School of Medicine)

Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22667-2

Suggested Citation

  • John-William Sidhom & H. Benjamin Larman & Drew M. Pardoll & Alexander S. Baras, 2021. "Author Correction: DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires," Nature Communications, Nature, vol. 12(1), pages 1-1, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22667-2
    DOI: 10.1038/s41467-021-22667-2
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    Cited by:

    1. Elliot H. Akama-Garren & Theo Broek & Lea Simoni & Carlos Castrillon & Cees E. Poel & Michael C. Carroll, 2021. "Follicular T cells are clonally and transcriptionally distinct in B cell-driven mouse autoimmune disease," Nature Communications, Nature, vol. 12(1), pages 1-19, December.
    2. Giancarlo Croce & Sara Bobisse & Dana Léa Moreno & Julien Schmidt & Philippe Guillame & Alexandre Harari & David Gfeller, 2024. "Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    3. Felix Drost & Yang An & Irene Bonafonte-Pardàs & Lisa M. Dratva & Rik G. H. Lindeboom & Muzlifah Haniffa & Sarah A. Teichmann & Fabian Theis & Mohammad Lotfollahi & Benjamin Schubert, 2024. "Multi-modal generative modeling for joint analysis of single-cell T cell receptor and gene expression data," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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