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  Model-based analysis of influenza A virus replication in genetically engineered cell lines elucidates the impact of host cell factors on key kinetic parameters of virus growth

Laske, T., Bachmann, M., Dostert, M., Karlas, A., Wirth, D., Frensing, T., et al. (2019). Model-based analysis of influenza A virus replication in genetically engineered cell lines elucidates the impact of host cell factors on key kinetic parameters of virus growth. PLoS Computational Biology, 15(4): e1006944. doi:10.1371/journal.pcbi.1006944.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-D594-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-E41E-9
Genre: Journal Article

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laske_3195927.pdf (Publisher version), 4MB
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Copyright: © 2019 Laske et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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 Creators:
Laske, Tanja1, Author              
Bachmann, Mandy1, Author              
Dostert, Melanie1, Author              
Karlas, Alexander2, Author
Wirth, Dagmar3, 4, Author
Frensing, Timo1, Author              
Meyer, Thomas F.2, Author
Hauser, Hansjörg3, Author
Reichl, Udo1, 5, Author              
Affiliations:
1Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738140              
2Max Planck Institute for Infection Biology, Berlin, Germany , ou_persistent22              
3Helmholtz Center for Infection Research, Braunschweig, Germany, ou_persistent22              
4Medical University Hannover, Hannover, Germany, ou_persistent22              
5Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156              

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Language(s): eng - English
 Dates: 2019
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1006944
Other: data_escidoc:3195927
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 15 (4) Sequence Number: e1006944 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1