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Publisher Correction: Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data

Author

Listed:
  • Yifan Zhao

    (School of Computer Science, McGill University
    Harvard-MIT Health Sciences and Technology)

  • Huiyu Cai

    (Peking University)

  • Zuobai Zhang

    (School of Computer Science, Fudan University)

  • Jian Tang

    (HEC Montreal)

  • Yue Li

    (School of Computer Science, McGill University)

Abstract

No abstract is available for this item.

Suggested Citation

  • Yifan Zhao & Huiyu Cai & Zuobai Zhang & Jian Tang & Yue Li, 2021. "Publisher Correction: Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data," Nature Communications, Nature, vol. 12(1), pages 1-1, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26140-y
    DOI: 10.1038/s41467-021-26140-y
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    File URL: https://www.nature.com/articles/s41467-021-26140-y
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    Cited by:

    1. Andrea Riba & Attila Oravecz & Matej Durik & Sara Jiménez & Violaine Alunni & Marie Cerciat & Matthieu Jung & Céline Keime & William M. Keyes & Nacho Molina, 2022. "Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Hao Chen & Frederick J. King & Bin Zhou & Yu Wang & Carter J. Canedy & Joel Hayashi & Yang Zhong & Max W. Chang & Lars Pache & Julian L. Wong & Yong Jia & John Joslin & Tao Jiang & Christopher Benner , 2024. "Drug target prediction through deep learning functional representation of gene signatures," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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