Diversity and complexity of HIV-1 drug resistance: a bioinformatics approach to predicting phenotype from genotype.

ABSTRACT: Drug resistance testing has been shown to be beneficial for clinical management of HIV type 1 infected patients. Whereas phenotypic assays directly measure drug resistance, the commonly used genotypic assays provide only indirect evidence of drug resistance, the major challenge being the interpretation of the sequence information. We analyzed the significance of sequence variations in the protease and reverse transcriptase genes for drug resistance and derived models that predict phenotypic resistance from genotypes. For 14 antiretroviral drugs, both genotypic and phenotypic resistance data from 471 clinical isolates were analyzed with a machine learning approach. Information profiles were obtained that quantify the statistical significance of each sequence position for drug resistance. Fo

SUBMITTER: Beerenwinkel N 

PROVIDER: S-EPMC123057 | biostudies-literature | 2002 Jun

REPOSITORIES: biostudies-literature