Protein secondary structure and homology by neural networks. The alpha-helices in rhodopsin.

@article{Bohr1988ProteinSS,
  title={Protein secondary structure and homology by neural networks. The alpha-helices in rhodopsin.},
  author={Henrik G. Bohr and Jakob Bohr and S\oren Brunak and Rodney M. J. Cotterill and Benny Lautrup and L N\orskov and Ole Hvilsted Olsen and Steffen B. Petersen},
  journal={FEBS letters},
  year={1988},
  volume={241 1-2},
  pages={223-8}
}
Neural networks provide a basis for semiempirical studies of pattern matching between the primary and secondary structures of proteins. Networks of the perceptron class have been trained to classify the amino-acid residues into two categories for each of three types of secondary feature: alpha-helix or not, beta-sheet or not, and random coil or not. The explicit prediction for the helices in rhodopsin is compared with both electron microscopy results and those of the Chou-Fasman method. A new… CONTINUE READING

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