Structure-mutagenicity modelling using counter propagation neural networks.

  title={Structure-mutagenicity modelling using counter propagation neural networks.},
  author={Marjan Vracko and Denise R. Mills and Subhash C. Basak},
  journal={Environmental toxicology and pharmacology},
  volume={16 1-2},
The set of 95 aromatic amines and their mutagenic potency was treated with counter propagation neural network, which enables analysis of self-organising maps (SOMs) and also the prediction of mutagenicity. Compounds were described with four classes of descriptors: topostructural (TS), topochemical (TC), geometrical, and quantum chemical (QC). The models were tested on their prediction ability with leave-one-out (LOO) cross-validation method. The squares of correlation coefficient lie between 0… CONTINUE READING

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Predicting mutagenicity of aromatic amines by various machine learning approaches.

Toxicological sciences : an official journal of the Society of Toxicology • 2010
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