Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1474-760X

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models ; volume:21 ; number:1 ; day:23 ; month:12 ; year:2020 ; pages:1-26 ; date:12.2020
Genome biology ; 21, Heft 1 (23.12.2020), 1-26, 12.2020

Creator: Garvin, Michael R.
T. Prates, Erica
Pavicic, Mirko
Jones, Piet
Amos, B. Kirtley
Geiger, Armin
Shah, Manesh B.
Streich, Jared
Felipe Machado Gazolla, Joao Gabriel
Kainer, David
Cliff, Ashley
Romero, Jonathon
Keith, Nathan
Brown, James B.
Jacobson, Daniel

Contributor: SpringerLink (Online service)

DOI: 10.1186/s13059-020-02191-0

URN: urn:nbn:de:101:1-2021013113255010748776

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:25 AM CEST

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Associated

Garvin, Michael R.
T. Prates, Erica
Pavicic, Mirko
Jones, Piet
Amos, B. Kirtley
Geiger, Armin
Shah, Manesh B.
Streich, Jared
Felipe Machado Gazolla, Joao Gabriel
Kainer, David
Cliff, Ashley
Romero, Jonathon
Keith, Nathan
Brown, James B.
Jacobson, Daniel
SpringerLink (Online service)

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Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models

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