Prediction of toxicity and data exploratory analysis of estrogen-active endocrine disruptors using counter-propagation artificial neural networks

Journal of Molecular Graphics and Modelling

Volumn 29, Issue 3, 2010, Pages 450-460

  Stojić, Nataša ^a   Erić, Slavica ^b   Kuzmanovski, Igor ^a  

^a SS CYRIL AND METHODIUS UNIVERSITY   (Macedonia)

^b UNIVERSITY OF BELGRADE   (Serbia)

Author keywords

Counter propagation artificial neural networks; Data exploratory analysis; Endocrine disruptors toxicity; Estrogenic activity prediction; QSAR; SAR

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ENDOCRINE DISRUPTOR; ESTROGENIC ACTIVITIES; EXPLORATORY ANALYSIS; QSAR; SAR;

CHEMICALS; DATA FLOW ANALYSIS; DATA HANDLING; FORECASTING; GENETIC ALGORITHMS; TOXICITY;

NEURAL NETWORKS;

ENDOCRINE DISRUPTOR; ESTROGEN;

ARTICLE; ARTIFICIAL NEURAL NETWORK; DATA ANALYSIS; ESTROGEN ACTIVITY; GENETIC ALGORITHM; PERFORMANCE; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; TOXICITY;

ALGORITHMS; ENDOCRINE DISRUPTORS; ESTROGENS; MODELS, MOLECULAR; MOLECULAR STRUCTURE; NEURAL NETWORKS (COMPUTER); PROTEIN CONFORMATION; RECEPTORS, ESTROGEN; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 78649522324     PISSN: 10933263     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmgm.2010.09.001     Document Type: Article

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