New workflow predicts drug targets against SARS-CoV-2 via metabolic changes in infected cells

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dc.contributor.author Leonidou, Nantia
dc.contributor.author Renz, Alina
dc.contributor.author Mostolizadeh, Reihaneh
dc.contributor.author Dräger, Andreas
dc.date.accessioned 2023-03-27T14:18:30Z
dc.date.available 2023-03-27T14:18:30Z
dc.date.issued 2023-03-23
dc.identifier.issn 1553-7358
dc.identifier.uri http://hdl.handle.net/10900/138651
dc.language.iso en de_DE
dc.publisher San Francisco, Calif. : Public Library of Science de_DE
dc.relation.uri https://doi.org/10.1371/journal.pcbi.1010903 de_DE
dc.subject host-virus interactions de_DE
dc.subject tissue-specific model de_DE
dc.subject antiviral targets de_DE
dc.subject flux balance analysis de_DE
dc.subject flux variability analysis de_DE
dc.subject reaction knockout de_DE
dc.subject host-derived enforcement de_DE
dc.subject metabolic modeling de_DE
dc.subject virus mutations de_DE
dc.subject nucleoside diphosphate kinase de_DE
dc.subject.classification Wirt , Viren , Interaktion , Modellierung , COVID-19 , SARS-CoV-2 , Wirkstoff , Stoffwechsel , Metabolismus , Mutation , Software Engineering , Python de_DE
dc.subject.ddc 004 de_DE
dc.subject.ddc 500 de_DE
dc.subject.ddc 570 de_DE
dc.subject.ddc 610 de_DE
dc.title New workflow predicts drug targets against SARS-CoV-2 via metabolic changes in infected cells de_DE
dc.type Artikel de_DE
utue.publikation.seiten E1010903 de_DE
utue.personen.roh Leonidou, Nantia
utue.personen.roh Renz, Alina
utue.personen.roh Mostolizadeh, Reihaneh
utue.personen.roh Dräger, Andreas
dcterms.isPartOf.ZSTitelID PLOS Computational Biology de_DE
dcterms.isPartOf.ZS-Issue 3 de_DE
dcterms.isPartOf.ZS-Volume 19 de_DE
utue.fakultaet 04 Medizinische Fakultät de_DE


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