Genetic programming for QSAR investigation of docking energy

Applied Soft Computing Journal

Volumn 10, Issue 1, 2010, Pages 170-182

  Archetti, Francesco ^a,b   Giordani, Ilaria ^a,c   Vanneschi, Leonardo ^a  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

^b Consorzio Milano Ricerche ^*  (Italy)

^c DELOS Srl   (Italy)

Author keywords

Computational biology; Docking energy; Drug design; Genetic Programming; Machine learning; QSAR; Regression

Indexed keywords

COMPUTATIONAL BIOLOGY; DOCKING ENERGY; DRUG DESIGN; MACHINE LEARNING; QSAR; REGRESSION;

BENCHMARKING; BINDING ENERGY; BIOCHEMISTRY; BIOINFORMATICS; COMPUTATIONAL METHODS; DOCKING; DRUG INTERACTIONS; DRUG THERAPY; EDUCATION; GENETIC ALGORITHMS; MACHINE DESIGN; MOLECULAR GRAPHICS; NEURAL NETWORKS; ORGANIC COMPOUNDS; REGRESSION ANALYSIS; ROBOT LEARNING; STATISTICS; SULFUR COMPOUNDS; TOXICITY;

GENETIC PROGRAMMING;

EID: 70350125156     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2009.06.013     Document Type: Article

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