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Article

Improvement of HIV-1 coreceptor tropism prediction by employing selected nucleotide positions of the env gene in a Bayesian network classifier.

The Journal of antimicrobial chemotherapy - 1 Jul 2013

Díez-Fuertes Francisco, Delgado Elena, Vega Yolanda, Fernández-García Aurora, Cuevas María Teresa, Pinilla Milagros, García Valentina, Pérez-Álvarez Lucía, Thomson Michael M

Abstract excerpt

OBJECTIVES: This study aimed to develop a genotypic method to predict HIV-1 coreceptor usage by employing the nucleotide sequence of the env gene in a tree-augmented naive Bayes (TAN) classifier, and to evaluate its accuracy in prediction compared with other available tools. METHODS: A wrapper data-mining strategy interleaved with a TAN algorithm was employed to evaluate the predictor value of every...

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Share to Computational Biology
Share to env Gene Products, Human Immunodeficiency Virus

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Share to Molecular Diagnostic Techniques

Share to Receptors, HIV

Share to Viral Tropism

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Source

Identifiers

PMID: 23511232
DOI: 10.1093/jac/dkt077

Genes

CCR5
CXCR4

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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