Application of two machine learning algorithms to genetic association studies in the presence of covariates

BMC Genetics

Volumn 9, Issue , 2008, Pages

  Nonyane, Bareng A S ^a   Foulkes, Andrea S ^a  

^a UNIVERSITY OF MASSACHUSETTS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIRETROVIRUS AGENT; HEPATIC LIPASE, HUMAN; HIGH DENSITY LIPOPROTEIN CHOLESTEROL; LIPG PROTEIN, HUMAN; TRIACYLGLYCEROL LIPASE;

ARTICLE; COHORT ANALYSIS; CONTROLLED STUDY; COVARIANCE; GENETIC ALGORITHM; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETIC SELECTION; GENETIC TRAIT; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS 1 INFECTION; INDIVIDUALITY; MACHINE LEARNING; MAJOR CLINICAL STUDY; MULTIVARIATE ADAPTIVE REGRESSION SPLINES; PREDICTION; PROCESS MODEL; RANDOM FOREST; THEORETICAL MODEL; ALGORITHM; ARTIFICIAL INTELLIGENCE; BIOLOGY; BLOOD; COMPUTER SIMULATION; ETHNOLOGY; GENETIC PREDISPOSITION; GENETICS; GENOTYPE; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; REGRESSION ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL;

HUMAN IMMUNODEFICIENCY VIRUS 1;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CHOLESTEROL, HDL; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENETIC PREDISPOSITION TO DISEASE; GENOTYPE; HIV INFECTIONS; HUMANS; LIPASE; MODELS, STATISTICAL; POLYMORPHISM, SINGLE NUCLEOTIDE; REGRESSION ANALYSIS;

EID: 58149343568     PISSN: None     EISSN: 14712156     Source Type: Journal    
DOI: 10.1186/1471-2156-9-71     Document Type: Article

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