Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain

Affiliation:	1. Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland;2. Botnar Research Centre for Child Health, Basel 4058, Switzerland;3. Alloy Therapeutics (Switzerland) AG, Basel 4058, Switzerland;4. Department of Biology, Institute of Microbiology and Immunology, ETH Zurich, Zurich 8093, Switzerland;5. Department of Pathology and Immunology, University of Geneva, Geneva 1211, Switzerland;6. Te Huataki Waiora School of Health, University of Waikato, Hamilton 3240, New Zealand

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Keywords:	directed evolution protein engineering machine learning deep learning artificial intelligence viral escape deep sequencing yeast display
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