Understanding the host-pathogen evolutionary balance through Gaussian process modeling of SARS-CoV-2.

Loguercio, Salvatore; Calverley, Ben C; Wang, Chao; Shak, Daniel; Zhao, Pei; Sun, Shuhong; Budinger, G R Scott; Balch, William E

Loguercio, Salvatore; Calverley, Ben C; Wang, Chao; Shak, Daniel; Zhao, Pei; Sun, Shuhong; Budinger, G R Scott; Balch, William E.

Afiliación

Loguercio S; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA.
Calverley BC; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA.
Wang C; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA.
Shak D; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA.
Zhao P; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA.
Sun S; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA.
Budinger GRS; Division of Pulmonary and Critical Care Medicine, Northwestern University, Chicago, IL, USA.
Balch WE; Department of Molecular Medicine, Scripps Research, La Jolla, CA, USA.

Patterns (N Y) ; 4(8): 100800, 2023 Aug 11.

Article en En | MEDLINE | ID: mdl-37602209

Palabras clave

Gaussian processes; SARS-CoV-2; early warning; evolution; genomic surveillance; host-pathogen; machine learning; spatial covariance

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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Patterns (N Y) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo

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PubMed Links

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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Patterns (N Y) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos