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  The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

Mann, J. K., Barton, J. P., Ferguson, A. L., Omarjee, S., Walker, B. D., Chakraborty, A., et al. (2014). The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing. PLoS Computational Biology, 10(8): e1003776. doi:10.1371/journal.pcbi.1003776.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0023-E096-A Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0023-E097-8
Genre: Journal Article

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PLOS_Comput_Biol_2014_10_e1003776.pdf (Publisher version), 688KB
 
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2014 Mann 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:
Mann, Jaclyn K., Author
Barton, John P., Author
Ferguson, Andrew L., Author
Omarjee, Saleha, Author
Walker, Bruce D., Author
Chakraborty, Arup, Author
Ndung'u, Thumbi1, Author           
Affiliations:
1Max-Planck Research Group Virology and Immunology, Max Planck Institute for Infection Biology, Max Planck Society, ou_2035285              

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Language(s): eng - English
 Dates: 2014-08-07
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1003776
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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: 10 (8) Sequence Number: e1003776 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1