@article{JRC31712,
	address = {Oxon (United Kingdom)},
	year = {2006},
	author = {Vracko Grobelsek M and Bandelj V and Barbieri P and Benfenati E and Chaudhry Q and Cronin M and Devillers J and Gallegos Saliner A and Gini G and Gramatica P and Helma C and Neagu D and Netzeva T and Pavan M and Tier G and Randic M and Worth A and Tsakovska I},
	abstract = {OECD adopted five principles for validation of QSAR models used for regulatory purposes. We present Kohonen neural networks and counter propagation neural networks, which are often used for QSAR modeling, in the light of these principles. As a case study we present a counter propagation network built on 541 compounds for modeling of toxicity toward fish fathead minnow.
		
		
		
		
		
		
		
		},
	title = {Validation of Counter Propagation Neural Network Models for Predictive Toxicology According to the OECD Principles. A Case Study},
	type = {},
	url = {},
	volume = {17},
	number = {3},
	journal = {SAR AND QSAR IN ENVIRONMENTAL RESEARCH},
	pages = {265-284},
	issn = {},
	publisher = {TAYLOR & FRANCIS INC},
	doi = {10.1080/10659360600787650}
}