Computational methods to predict the mutational landscape of the spike protein. | Biophys J;120(14): 2763-2765, 2021 07 20. | MEDLINE

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Computational methods to predict the mutational landscape of the spike protein.

Paci, Emanuele; Ross, James F.

Paci E; Astbury Centre and School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom. Electronic address: e.paci@leeds.ac.uk.
Ross JF; Astbury Centre and School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom.

Biophys J ; 120(14): 2763-2765, 2021 07 20.

Article in English | MEDLINE | ID: covidwho-1353368

Subject(s)

Genetic Fitness; Spike Glycoprotein, Coronavirus; Humans; Mutation; Spike Glycoprotein, Coronavirus/genetics

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genetic Fitness / Spike Glycoprotein, Coronavirus Type of study: Prognostic study Limits: Humans Language: English Journal: Biophys J Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genetic Fitness / Spike Glycoprotein, Coronavirus Type of study: Prognostic study Limits: Humans Language: English Journal: Biophys J Year: 2021 Document Type: Article