Particle swarm optimization and genetic algorithm as feature selection techniques for the QSAR modeling of imidazo[1,5-a]pyrido[3,2-e]pyrazines, inhibitors of phosphodiesterase 10A

Chemical Biology and Drug Design

Volumn 82, Issue 6, 2013, Pages 685-696

  Goodarzi, Mohammad ^a   Saeys, Wouter ^a   Deeb, Omar ^b   Pieters, Sigrid ^c   Vander Heyden, Yvan ^c  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b AL QUDS UNIVERSITY   (Palestine)

^c VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

Author keywords

Euclidean distance; Genetic algorithm; Locally weighted regression; Mahalanobis distance; Multiple linear regression; Particle swarm optimization

Indexed keywords

IMIDAZO[1,5 A]PYRIDO[3,2 E]PYRAZINE DERIVATIVE; PHOSPHODIESTERASE INHIBITOR; UNCLASSIFIED DRUG;

ARTICLE; CHEMICAL STRUCTURE; CHEMOMETRIC ANALYSIS; CORRELATION COEFFICIENT; GENETIC ALGORITHM; IC 50; MATHEMATICAL ANALYSIS; MULTIPLE LINEAR REGRESSION ANALYSIS; PARTICLE SWARM OPTIMIZATION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTUM CHEMISTRY;

EUCLIDEAN DISTANCE; GENETIC ALGORITHM; LOCALLY WEIGHTED REGRESSION; MAHALANOBIS DISTANCE; MULTIPLE LINEAR REGRESSION; PARTICLE SWARM OPTIMIZATION;

ALGORITHMS; HUMANS; IMIDAZOLES; MODELS, MOLECULAR; PHOSPHODIESTERASE INHIBITORS; PHOSPHORIC DIESTER HYDROLASES; PROTEIN BINDING; PYRAZINES; PYRIDINES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84889884834     PISSN: 17470277     EISSN: 17470285     Source Type: Journal    
DOI: 10.1111/cbdd.12196     Document Type: Article

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