Characterizing the Relationship Between HIV‐1 Genotype and Phenotype: Prediction‐Based Classification | Zendy

Foulkes A. S. | Zendy; Gruttola V. De | Zendy

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Characterizing the Relationship Between HIV‐1 Genotype and Phenotype: Prediction‐Based Classification

Author(s) -

Foulkes A. S.,

Gruttola V. De

Publication year - 2002

Publication title -

biometrics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.298

H-Index - 130

eISSN - 1541-0420

pISSN - 0006-341X

DOI - 10.1111/j.0006-341x.2002.00145.x

Subject(s) - linear discriminant analysis , genotype , indinavir , human immunodeficiency virus (hiv) , disease , set (abstract data type) , phenotype , computational biology , antiretroviral therapy , computer science , artificial intelligence , statistics , machine learning , biology , mathematics , medicine , genetics , viral load , virology , gene , programming language

Summary. This paper establishes a framework for understanding the complex relationships between HIV‐1 genotypic markers of resistance to antiretroviral drugs and clinical measures of disease progression. A new classification scheme based on the probabilities of how new patients will respond to antiretroviral therapy given the available data is proposed as a method for distinguishing among groups of viral sequences. This approach draws from existing cluster analysis, discriminant analysis, and recursive partitioning techniques and requires a model relating genotypic characteristics to phenotypic response. A data set of 2746 sequences and the corresponding Indinavir 50% inhibitory concentrations are described and used for illustrative purposes.

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