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The HIV positive selection mutation database

The HIV positive selection mutation database is a large-scale database available at that provides detailed selection pressure maps of HIV protease and reverse transcriptase, both of which are molecular targets of antiretroviral therapy. This database makes available for the first time a very large H...

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Detalles Bibliográficos
Autores principales: Pan, Calvin, Kim, Joseph, Chen, Lamei, Wang, Qi, Lee, Christopher
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1669717/
https://www.ncbi.nlm.nih.gov/pubmed/17108357
http://dx.doi.org/10.1093/nar/gkl855
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author Pan, Calvin
Kim, Joseph
Chen, Lamei
Wang, Qi
Lee, Christopher
author_facet Pan, Calvin
Kim, Joseph
Chen, Lamei
Wang, Qi
Lee, Christopher
author_sort Pan, Calvin
collection PubMed
description The HIV positive selection mutation database is a large-scale database available at that provides detailed selection pressure maps of HIV protease and reverse transcriptase, both of which are molecular targets of antiretroviral therapy. This database makes available for the first time a very large HIV sequence dataset (sequences from ∼50 000 clinical AIDS samples, generously contributed by Specialty Laboratories, Inc.), which makes possible high-resolution selection pressure mapping. It provides information about not only the selection pressure on individual sites but also how selection pressure at one site is affected by mutations on other sites. It also includes datasets from other public databases, namely the Stanford HIV database [S. Y. Rhee, M. J. Gonzales, R. Kantor, B. J. Betts, J. Ravela and R. W. Shafer (2003) Nucleic Acids Res., 31, 298–303]. Comparison between these datasets in the database enables cross-validation with independent datasets and also specific evaluation of the effect of drug treatment.
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spelling pubmed-16697172007-06-26 The HIV positive selection mutation database Pan, Calvin Kim, Joseph Chen, Lamei Wang, Qi Lee, Christopher Nucleic Acids Res Articles The HIV positive selection mutation database is a large-scale database available at that provides detailed selection pressure maps of HIV protease and reverse transcriptase, both of which are molecular targets of antiretroviral therapy. This database makes available for the first time a very large HIV sequence dataset (sequences from ∼50 000 clinical AIDS samples, generously contributed by Specialty Laboratories, Inc.), which makes possible high-resolution selection pressure mapping. It provides information about not only the selection pressure on individual sites but also how selection pressure at one site is affected by mutations on other sites. It also includes datasets from other public databases, namely the Stanford HIV database [S. Y. Rhee, M. J. Gonzales, R. Kantor, B. J. Betts, J. Ravela and R. W. Shafer (2003) Nucleic Acids Res., 31, 298–303]. Comparison between these datasets in the database enables cross-validation with independent datasets and also specific evaluation of the effect of drug treatment. Oxford University Press 2007-01 2006-11-15 /pmc/articles/PMC1669717/ /pubmed/17108357 http://dx.doi.org/10.1093/nar/gkl855 Text en © 2006 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Pan, Calvin
Kim, Joseph
Chen, Lamei
Wang, Qi
Lee, Christopher
The HIV positive selection mutation database
title The HIV positive selection mutation database
title_full The HIV positive selection mutation database
title_fullStr The HIV positive selection mutation database
title_full_unstemmed The HIV positive selection mutation database
title_short The HIV positive selection mutation database
title_sort hiv positive selection mutation database
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1669717/
https://www.ncbi.nlm.nih.gov/pubmed/17108357
http://dx.doi.org/10.1093/nar/gkl855
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