Author: Thomas Desautels; Adam Zemla; Edmond Lau; Magdalena Franco; Daniel Faissol
Title: Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing Document date: 2020_4_10
ID: kg2j0dqy_24
Snippet: . CC-BY 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.03.024885 doi: bioRxiv preprint with SARS-CoV-1. These results suggest that these M396-derived antibody mutants potentially bind and neutralize SARS-CoV-2......
Document: . CC-BY 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.03.024885 doi: bioRxiv preprint with SARS-CoV-1. These results suggest that these M396-derived antibody mutants potentially bind and neutralize SARS-CoV-2.
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