dollars/chemical / self-organising data mining technology / data mining tool / even dedicated experts systems / workflow processing / adequate dimension reduction tool / chemicals inducing toxicity / Soft computing / data mining algorithm / Self-organising data mining / data mining / occupied molecular orbital energy / data pre-processing / data mining algorithms / chemical / real-world systems / chemicals / ecotoxicological systems / learning algorithm / energy / /
Organization
MIT / /
Person
Predictive Carcinogenicity / Figure / /
Position
model / model in our initial analysis / /
Product
M-16 / /
ProgrammingLanguage
DC / /
ProvinceOrState
California / /
Technology
self-organising data mining technology / learning algorithm / Neural Network / data mining algorithms / Data Mining / simulation / data mining algorithm / /
Carcinogenicity Prediction of Aromatic Compounds Using Self-organising Data Mining Frank LEMKE*, Emilio BENFENATI** *KnowledgeMiner Software, Germany ** Istituto di Ricerche Farmacologiche "Mario Negri", Italy