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

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

Author: Leonidou, Nantia; Renz, Alina; Mostolizadeh, Reihaneh; Dräger, Andreas
Tübinger Autor(en):
Leonidou, Nantia
Renz, Alina
Mostolizadeh, Reihaneh
Dräger, Andreas
Published in: PLOS Computational Biology (2023-03-23), Bd. 19, H. 3, S. E1010903
Verlagsangabe: San Francisco, Calif. : Public Library of Science
Language: English
Full text: https://doi.org/10.1371/journal.pcbi.1010903
ISSN: 1553-7358
DDC Classifikation: 004 - Data processing and computer science
500 - Natural sciences and mathematics
570 - Life sciences; biology
610 - Medicine and health
Keywords: Wirt , Viren , Interaktion , Modellierung , COVID-19 , SARS-CoV-2 , Wirkstoff , Stoffwechsel , Metabolismus , Mutation , Software Engineering , Python
Dokumentart: Article
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