Prediction of Modes of Toxic Action and toxicity of phenols with feature selection algorithms coupled with fuzzy ARTMAP

Descriptors suitable for the discrimination of four modes of toxic action (MOA) of 221 phenols with respect to the ciliate Tetrahymena pyriformis were selected by using SOM-dissimilarity measures and other well-known feature selection techniques. The performance of these methods and of ensembles of them to predict MOA classes and the toxicity log[1/IGC(50)] (mmol/ L) for each action mechanism when coupled with a fuzzy-ARTMAP neural network were assessed.

Rallo, R.,Espinosa, G., and F. Giralt. Prediction of Modes of Toxic Action and toxicity of phenols with feature selection algorithms coupled with fuzzy ARTMAP Proceedings of the Joint Meeting on Medicinal Chemistry, Vienna, Eds. P. Ettmayer and G. Ecker, Medimont SRL, F620C0176, 27-33. (ISBN 88-7587-163-9)

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About robertrallo

Associate Professor, Dept. d'Eng. Informàtica i Matemàtiques at URV; Director of BioCENIT, Bioinformatics & Computational Environmental Engineering Research Team at URV; Member of ATIC, Advanced Technology & Innovation Center at URV; Visiting Scholar at UCLA; Member of the WaTeR center, UCLA; Member of the Center for Environmental Implications of Nanotechnology (CEIN), UCLA; Member of the Center for Nanobiology and Predictive Toxicology (CNPT), UCLA.

Posted on June 20, 2005, in Uncategorized and tagged , , . Bookmark the permalink. Leave a comment.

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