TRM: A Powerful Two-Stage Machine Learning Approach for Identifying SNP-SNP Interactions

Annals of Human Genetics

Volumn 76, Issue 1, 2012, Pages 53-62

  Lin, Hui Yi ^a   Ann Chen, Y ^a   Tsai, Ya Yu ^a   Qu, Xiaotao ^a   Tseng, Tung Sung ^b   Park, Jong Y ^a  

^a H LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE   (United States)

^b LOUISIANA STATE UNIVERSITY HEALTH SCIENCES CENTER   (United States)

Author keywords

Interaction; Machine learning; Polymorphism

Indexed keywords

ARTICLE; CONTROLLED STUDY; GENETIC VARIABILITY; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MOLECULAR GENETICS; MULTIVARIATE ADAPTIVE REGRESSION SPLINE; PRIORITY JOURNAL; RANDOM FOREST; SINGLE NUCLEOTIDE POLYMORPHISM;

ARTIFICIAL INTELLIGENCE; DECISION TREES; GENOTYPE; HUMANS; MALE; MODELS, GENETIC; MODELS, STATISTICAL; POLYMORPHISM, SINGLE NUCLEOTIDE; PROSTATIC NEOPLASMS; RECEPTORS, ESTROGEN;

EID: 84155163036     PISSN: 00034800     EISSN: 14691809     Source Type: Journal    
DOI: 10.1111/j.1469-1809.2011.00692.x     Document Type: Article

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