Update of the Drug Resistance Mutations in HIV-1.

By Victoria A. Johnson, F. Brun-Vézinet, B. Clotet, H. Gunthard, D. R. Kuritzkes, Deenan Pillay, J. Schapiro, D. Richman. 2008

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Citations in the corpus

Bayesian network analysis of resistance pathways against HIV-1 protease inhibitors. (2007, background): “Within the study of drug resistance, one often refers to a mutation that is selected as a first mutation as a major mutation (Shafer, 2002; Johnson et al., 2004).”
History-alignment models for bias-aware prediction of virological response to HIV combination therapy (2012, methodology): “The information on the viral genotype is given in terms of a binary vector indicating the presence (1) or absence (0) of a set of predefined resistance-relevant mutations derived from the list given in Johnson et al. (2008).”
Special Contribution 2014 Update of the Drug Resistance Mutations in HIV-1 (2014, background): “cludes: (1) assessing whether the pattern or absence of a pattern in the mutations is consistent with the patient’s antiretroviral therapy history; (2) recognizing that in the absence of drug (selection pressure), resistant strains may be present at levels below the limit of detection of the test (a”
Multi-task learning for HIV therapy screening (2008, methodology): “We use the viral genotype taken from the patient shortly before the treatment and represent it by a binary vector indicating the presence of resistance-relevant mutations of the viral sequence (Johnson et al., 2007).”
High rates of forward transmission events after acute/early HIV-1 infection. (2007, unknown): “tional AIDS Society–USA resistance panel guidelines [21].”
Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment (2008, background): “The number of HIV-1 mutations considered to be associated with drug resistance, as indicated by the reference International AIDS Society (IAS) list [5], has increased with the expanding arsenal of available drugs.”