Machine learning identifies molecular regulators and therapeutics for targeting SARS-CoV2-induced cytokine release.

Chan, Marina; Vijay, Siddharth; McNevin, John; McElrath, M Juliana; Holland, Eric C; Gujral, Taranjit S

Chan, Marina; Vijay, Siddharth; McNevin, John; McElrath, M Juliana; Holland, Eric C; Gujral, Taranjit S.

Affiliation

Chan M; Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Vijay S; Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
McNevin J; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
McElrath MJ; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Holland EC; Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Gujral TS; Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

Mol Syst Biol ; 17(9): e10426, 2021 09.

Article in En | MEDLINE | ID: mdl-34486798

Subject(s)
Key words

N-terminal domain; Ponatinib; SARS-CoV-2; kinases; machine learning

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Antiviral Agents / Cytokines / Host-Pathogen Interactions Limits: Animals / Humans / Male Language: En Journal: Mol Syst Biol Journal subject: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Year: 2021 Document type: Article Affiliation country: Estados Unidos Country of publication: Reino Unido

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