@article{CordesKaiserSelbig2006,
  author    = {Cordes, Frank and Kaiser, Rolf and Selbig, Joachim},
  title     = {Bioinformatics approach to predicting HIV drug resistance},
  issn      = {1473-7159},
  doi       = {10.1586/14737159.6.2.207},
  year      = {2006},
  abstract  = {The emergence of drug resistance remains one of the most challenging issues in the treatment of HIV-1 infection. The extreme replication dynamics of HIV facilitates its escape from the selective pressure exerted by the human immune system and by the applied combination drug therapy. This article reviews computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genotypic and phenotypic data. Genotypic assays are based on the analysis of mutations associated with reduced drug susceptibility, but are difficult to interpret due to the numerous mutations and mutational patterns that confer drug resistance. Phenotypic resistance or susceptibility can be experimentally evaluated by measuring the inhibition of the viral replication in cell culture assays. However, this procedure is expensive and time consuming},
  language  = {en}
}
@article{BeerenwinkelSingLengaueretal.2005,
  author    = {Beerenwinkel, Niko and Sing, Tobias and Lengauer, Thomas and Rahnenfuhrer, Joerg and Roomp, Kirsten and Savenkov, Igor and Fischer, Roman and Hoffmann, Daniel and Selbig, Joachim and Korn, Klaus and Walter, Hauke and Berg, Thomas and Braun, Patrick and Faetkenheuer, Gerd and Oette, Mark and Rockstroh, Juergen and Kupfer, Bernd and Kaiser, Rolf and Daeumer, Martin},
  title     = {Computational methods for the design of effective therapies against drug resistant HIV strains},
  year      = {2005},
  abstract  = {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},
  language  = {en}
}