Protein secondary structure prediction with a neural network.

  title={Protein secondary structure prediction with a neural network.},
  author={L. Howard Holley and Martin Karplus},
  journal={Proceedings of the National Academy of Sciences of the United States of America},
  volume={86 1},
A method is presented for protein secondary structure prediction based on a neural network. A training phase was used to teach the network to recognize the relation between secondary structure and amino acid sequences on a sample set of 48 proteins of known structure. On a separate test set of 14 proteins of known structure, the method achieved a maximum overall predictive accuracy of 63% for three states: helix, sheet, and coil. A numerical measure of helix and sheet tendency for each residue… CONTINUE READING
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