Predicting gene function using hierarchical multi-label decision tree ensembles

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Schietgat, Leander ^a   Vens, Celine ^a   Struyf, Jan ^a   Blockeel, Hendrik ^a   Kocev, Dragi ^b   Džeroski, Sašo ^b  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b JO EF STEFAN INSTITUTE   (Slovenia)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL FUNCTIONS; COMPUTATIONALLY EFFICIENT; FUNCTION PREDICTION; MACHINE LEARNING METHODS; PREDICTIVE PERFORMANCE; STATISTICAL LEARNING; STATISTICAL LEARNING METHODS; TREE-BASED METHODS;

ALGORITHMS; DATA MINING; FORECASTING; GENES; LEARNING SYSTEMS; TREES (MATHEMATICS);

DECISION TREES;

ARABIDOPSIS THALIANA; MUS MUSCULUS; SACCHAROMYCES CEREVISIAE;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGY; DECISION TREE; GENE; GENE EXPRESSION PROFILING; GENETICS; METHODOLOGY; OPEN READING FRAME;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DECISION TREES; GENE EXPRESSION PROFILING; GENES; OPEN READING FRAMES;

EID: 77349119213     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-2     Document Type: Article

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