Dealing with sparse data in predicting outcomes of HIV combination therapies-Reference-Cited by-同舟云学术

Dealing with sparse data in predicting outcomes of HIV combination therapies

Published:2010-07-12 Issue:17 Volume:26 Page:2085-2092
ISSN:1460-2059
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Bogojeska Jasmina,Bickel Steffen,Altmann André,Lengauer Thomas

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/26/17/2085/16895046/btq361.pdf

Reference19 articles.

1. Improved prediction of response to antiretroviral combination therapy using the genetic barrier to drug resistance;Altmann;Antivir. Ther.,2007

2. Advantages of predicted phenotypes and statistical learning models in inferring virological response to antiretroviral therapy from hiv genotype;Altmann;Antivir. Ther.,2009

3. Predicting response to combination antiretroviral therapy: retrospective validation of geno2pheno-theo on a large clinical database;Altmann;J. Infect. Dis.,2009

4. Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes;Beerenwinkel;Nucleic Acids Res.,2003

5. Methods for optimizing antiviral combination therapies;Beerenwinkel;Bioinformatics,2003

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