Title :
Geno2pheno: interpreting genotypic HIV drug resistance tests
Author :
Beerenwinkel, Niko ; Lengauer, Thomas ; Selbig, Joachim ; Schmidt, Barbara ; Walter, Hauke ; Korn, Klaus ; Kaiser, Rolf ; Hoffmann, Daniel
Author_Institution :
Fraunhofer Inst for Algorithms & Sci. Comput., Frankfurt, Germany
Abstract :
This intelligent system uses information encoded in the HIV genomic sequence to predict the virus´s resistance or susceptibility to drugs. To make predictions, geno2pheno employs decision tree classifiers and support vector machines.
Keywords :
biology computing; decision trees; learning (artificial intelligence); learning automata; medical computing; microorganisms; patient treatment; sequences; HIV genomic sequence; decision tree classifiers; drug susceptibility; geno2pheno; genotypic HIV drug resistance test interpretation; intelligent system; support vector machines; Bioinformatics; Classification tree analysis; Decision trees; Drugs; Genomics; Human immunodeficiency virus; Intelligent systems; Machine intelligence; Support vector machines; Testing;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/5254.972080
