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

Leonidou, Nantia; Renz, Alina; Mostolizadeh, Reihaneh; Dräger, Andreas

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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	Article	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