Data-mining methods as useful tools for predicting individual drug response: Application to CYP2D6 data

Human Heredity

Volumn 62, Issue 3, 2006, Pages 119-134

  Sabbagh, Audrey ^a,b   Darlu, Pierre ^a  

^a INSERM   (France)

^b HÔPITAL PAUL BROUSSE   (France)

Author keywords

Artificial neural network; CYP2D6; Decision tree; Marker selection; Multifactor dimensionality reduction; Random forests

Indexed keywords

BIOLOGICAL MARKER; CYTOCHROME P450 2D6;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; DECISION THEORY; DRUG METABOLISM; DRUG RESPONSE; ETHNIC DIFFERENCE; EVALUATION; GENETIC POLYMORPHISM; GENOTYPE; HAPLOTYPE; HUMAN; HUMAN EXPERIMENT; INFORMATION PROCESSING; NORMAL HUMAN; PATTERN RECOGNITION; PHARMACOGENETICS; POPULATION RESEARCH; PREDICTION; SAMPLE; TREATMENT OUTCOME; TREATMENT PLANNING;

CYTOCHROME P-450 CYP2D6; ETHNIC GROUPS; FEASIBILITY STUDIES; GENE FREQUENCY; GENETIC MARKERS; GENOTYPE; HUMANS; LINKAGE DISEQUILIBRIUM; NEURAL NETWORKS (COMPUTER); PHARMACOGENETICS; PHENOTYPE; POLYMORPHISM, GENETIC;

EID: 33751074460     PISSN: 00015652     EISSN: None     Source Type: Journal    
DOI: 10.1159/000096416     Document Type: Article

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