Virginia Commonwealth University / National Library of Medicine’s Toxicology Data Network / University of North Carolina / Chapel Hill / Eastern Nazarene College / Hall et al. / / /
IndustryTerm
chemical substructures / networks / lico software / polycyclic aromatic ring systems / tree-based classifica tion algorithm / sphere exclusion algorithm / chemical compounds / Expert systems / pharmaceuticals / genetic algorithm / Structural and chemical diversity / chemical sub structures / back-propagation neural network / chemical entities / Rule-based systems / optimized minimum energy conformation / overall algorithm / chemical agents / chemical structure / stochastic search / learning algorithm / learning algorithms / phylogenetic tree-like algorithm / /
MarketIndex
set 10 / /
NaturalFeature
Decision Forest / /
Organization
Virginia Commonwealth University / UK Environmental Mutagen Society / Department of Chemistry / School of Pharmacy / Division of Medicinal Chemistry and Natural Products / National Center for Toxicological Research / University of North Carolina / Chapel Hill / Eastern Nazarene College / Division of Biometry and Risk Assessment / /
Person
Amine / Bush / ANN DF / Marc Parham / / /
Position
kNN QSAR model / Model development starts / Model development Model / King / model development process / Model / representative / model kNN model / model development the same set / /
ProvinceOrState
Virginia / Alaska / North Carolina / Massachusetts / /
Mutagenesis vol. 19 no. 5 pp[removed], 2004 doi:[removed]mutage/geh043 Three new consensus QSAR models for the prediction of Ames genotoxicity