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Compositional perturbation autoencoder for single-cell response modeling

View ORCID ProfileMohammad Lotfollahi, View ORCID ProfileAnna Klimovskaia Susmelj, Carlo De Donno, Yuge Ji, Ignacio L. Ibarra, F. Alexander Wolf, Nafissa Yakubova, Fabian J. Theis, David Lopez-Paz
doi: https://doi.org/10.1101/2021.04.14.439903
Mohammad Lotfollahi
1Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
3School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
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  • ORCID record for Mohammad Lotfollahi
Anna Klimovskaia Susmelj
2Facebook AI, 6 Rue Ménars, Paris, 75002, France
5Swiss Data Science Center, Zurich, Switzerland
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  • ORCID record for Anna Klimovskaia Susmelj
Carlo De Donno
1Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
7Department of Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich, Bavaria, Germany
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Yuge Ji
1Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
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Ignacio L. Ibarra
1Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
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F. Alexander Wolf
1Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
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Nafissa Yakubova
2Facebook AI, 6 Rue Ménars, Paris, 75002, France
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Fabian J. Theis
1Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
3School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
4Department of Mathematics, Technical University of Munich, Munich, Munich, Germany
6Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
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  • For correspondence: fabian.theis@helmholtz-muenchen.de
David Lopez-Paz
2Facebook AI, 6 Rue Ménars, Paris, 75002, France
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Article Information

doi 
https://doi.org/10.1101/2021.04.14.439903
History 
  • April 15, 2021.

Article Versions

  • You are currently viewing Version 1 of this article (April 15, 2021 - 23:28).
  • View Version 2, the most recent version of this article.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Author Information

  1. Mohammad Lotfollahi1,3,✶,
  2. Anna Klimovskaia Susmelj2,5,✶,
  3. Carlo De Donno1,7,✶✶,
  4. Yuge Ji1,✶✶,
  5. Ignacio L. Ibarra1,
  6. F. Alexander Wolf1,∘,
  7. Nafissa Yakubova2,
  8. Fabian J. Theis1,3,4,6,‡ and
  9. David Lopez-Paz2
  1. 1Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
  2. 2Facebook AI, 6 Rue Ménars, Paris, 75002, France
  3. 3School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
  4. 4Department of Mathematics, Technical University of Munich, Munich, Munich, Germany
  5. 5Swiss Data Science Center, Zurich, Switzerland
  6. 6Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  7. 7Department of Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich, Bavaria, Germany
  1. ↵‡Correspondence to fabian.theis{at}helmholtz-muenchen.de
  1. ↵✶ These authors contributed equally to the work

  2. ↵✶✶ These authors contributed equally to the work

  • ↵∘ Cellarity, Inc., Cambridge, MA.

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Posted April 15, 2021.
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Compositional perturbation autoencoder for single-cell response modeling
Mohammad Lotfollahi, Anna Klimovskaia Susmelj, Carlo De Donno, Yuge Ji, Ignacio L. Ibarra, F. Alexander Wolf, Nafissa Yakubova, Fabian J. Theis, David Lopez-Paz
bioRxiv 2021.04.14.439903; doi: https://doi.org/10.1101/2021.04.14.439903
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Compositional perturbation autoencoder for single-cell response modeling
Mohammad Lotfollahi, Anna Klimovskaia Susmelj, Carlo De Donno, Yuge Ji, Ignacio L. Ibarra, F. Alexander Wolf, Nafissa Yakubova, Fabian J. Theis, David Lopez-Paz
bioRxiv 2021.04.14.439903; doi: https://doi.org/10.1101/2021.04.14.439903

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