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Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing

Thomas Desautels, Adam Zemla, Edmond Lau, Magdalena Franco, Daniel Faissol
doi: https://doi.org/10.1101/2020.04.03.024885

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doi 
https://doi.org/10.1101/2020.04.03.024885
History 
  • April 10, 2020.
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 4.0 International license.

Author Information

  1. Thomas Desautels,
  2. Adam Zemla,
  3. Edmond Lau,
  4. Magdalena Franco and
  5. Daniel Faissol2
  1. Lawrence Livermore National Laboratory
  1. ↵2Correspondence to: dfaissol{at}llnl.gov
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Posted April 10, 2020.
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Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing
Thomas Desautels, Adam Zemla, Edmond Lau, Magdalena Franco, Daniel Faissol
bioRxiv 2020.04.03.024885; doi: https://doi.org/10.1101/2020.04.03.024885
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