A General QSAR Model for Predicting the Toxicity of Organic Chemicals to Luminescent Bacteria (Microtox® test)

Abstract
A large data set of Microtox® toxicity results was used to derive a general QSAR model. Chemicals were described by means of a modified autocorrelation method. The autocorrelation vectors were generated from atomic contributions encoding the hydrophobicity and molar refractivity of the molecules. A three-layer backpropagation neural network was used to design the model. The obtained results were compared with those obtained from a principal components regression analysis.

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