The learned symmetry concept in revealing quantitative structure-activity relationships with artificial neural networks.

Abstract

A method to build QSAR models based on substituent constants for congeneric sets of compounds having several topologically equivalent substituent positions was proposed. The approach is based on the application of artificial neural networks (learning to construct nonlinear structure-activity relationships taking into account necessary symmetry properties of… (More)

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Cite this paper

@article{Baskin2001TheLS, title={The learned symmetry concept in revealing quantitative structure-activity relationships with artificial neural networks.}, author={Igor I. Baskin and N M Halberstam and T. V. Mukhina and V. A. Palyulin and N. S. Zefirov}, journal={SAR and QSAR in environmental research}, year={2001}, volume={12 4}, pages={401-16} }