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/IGC50] (mmol/L) for each action mechanism when coupled with a fuzzyARTMAP neural network were assessed.