Neural Network Modeling for Estimation of Partition Coefficient Based on Atom-Type Electrotopological State Indices

@article{Huuskonen2000NeuralNM,
  title={Neural Network Modeling for Estimation of Partition Coefficient Based on Atom-Type Electrotopological State Indices},
  author={Jarmo J. Huuskonen and David J. Livingstone and Igor V. Tetko},
  journal={Journal of chemical information and computer sciences},
  year={2000},
  volume={40 4},
  pages={947-55}
}
A method for predicting log P values for a diverse set of 1870 organic molecules has been developed based on atom-type electrotopological-state (E-state) indices and neural network modeling. An extended set of E-state indices, which included specific indices with a more detailed description of amino, carbonyl, and hydroxy groups, was used in the current study. For the training set of 1754 molecules the squared correlation coefficient and root-mean-squared error were r2 = 0.90 and RMS(LOO) = 0… CONTINUE READING
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