Skip Navigation


Bioinformatics Advance Access originally published online on September 6, 2005
Bioinformatics 2005 21(21):3943-3950; doi:10.1093/bioinformatics/bti654
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrowOA All Versions of this Article:
21/21/3943    most recent
bti654v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (15)
Google Scholar
Right arrow Articles by Beerenwinkel, N.
Right arrow Articles by Däumer, M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Beerenwinkel, N.
Right arrow Articles by Däumer, M.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oxfordjournals.org

Computational methods for the design of effective therapies against drug resistant HIV strains

Niko Beerenwinkel 1,*, Tobias Sing 2, Thomas Lengauer 2, Jörg Rahnenführer 2, Kirsten Roomp 2, Igor Savenkov 2, Roman Fischer 3, Daniel Hoffmann 3, Joachim Selbig 4, Klaus Korn 5, Hauke Walter 5, Thomas Berg 6, Patrick Braun 7, Gerd Fätkenheuer 8, Mark Oette 10, Jürgen Rockstroh 11, Bernd Kupfer 12, Rolf Kaiser 9 and Martin Däumer 9

1Department of Mathematics, University of California Berkeley, CA, USA
2Max Planck Institute for Informatics Saarbrücken, Germany
3Center of Advanced European Studies and Research Bonn, Germany
4Max Planck Institute of Molecular Plant Physiology and University of Potsdam Germany
5Institute of Clinical and Molecular Virology, University of Erlangen-Nürnberg Erlangen, Germany
6Medical Laboratory Berlin, Germany
7PZB Aachen, Germany
8Department of Internal Medicine, University of Cologne Germany
9Institute of Virology, University of Cologne Germany
10Department of Gastroenterology, University of Düsseldorf Germany
11Department of Internal Medicine, University of Bonn Germany
12Institute of Medical Microbiology and Immunology, University of Bonn Germany

*To whom correspondence should be addressed.

Summary: The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data.

Contact: niko{at}math.berkeley.edu


Received on June 8, 2005; revised on July 27, 2005; accepted on August 30, 2005

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
BioinformaticsHome page
K. Deforche, R. Camacho, K. Van Laethem, P. Lemey, A. Rambaut, Y. Moreau, and A.-M. Vandamme
Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment
Bioinformatics, January 1, 2008; 24(1): 34 - 41.
[Abstract] [Full Text] [PDF]


Home page
BiostatisticsHome page
N. Beerenwinkel and M. Drton
A mutagenetic tree hidden Markov model for longitudinal clonal HIV sequence data
Biostat., January 1, 2007; 8(1): 53 - 71.
[Abstract] [Full Text] [PDF]



Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.