Prediction of the disulfide bonding state of cysteines in proteins with hidden neural networks.

@article{Martelli2002PredictionOT,
  title={Prediction of the disulfide bonding state of cysteines in proteins with hidden neural networks.},
  author={Pier Luigi Martelli and Piero Fariselli and Luca Malaguti and Rita Casadio},
  journal={Protein engineering},
  year={2002},
  volume={15 12},
  pages={951-3}
}
A hybrid system (hidden neural network) based on a hidden Markov model (HMM) and neural networks (NN) was trained to predict the bonding states of cysteines in proteins starting from the residue chains. Training was performed using 4136 cysteine-containing segments extracted from 969 non-homologous proteins of well-resolved 3D structure and without chain-breaks. After a 20-fold cross-validation procedure, the efficiency of the prediction scores as high as 80% using neural networks based on… CONTINUE READING

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