Peptide sequence determination from high-energy collision-induced dissociation spectra using artificial neural networks

@article{Scarberry1995PeptideSD,
  title={Peptide sequence determination from high-energy collision-induced dissociation spectra using artificial neural networks},
  author={R. Scarberry and Z. Zhang and D. Knapp},
  journal={Journal of the American Society for Mass Spectrometry},
  year={1995},
  volume={6},
  pages={947-961}
}
  • R. Scarberry, Z. Zhang, D. Knapp
  • Published 1995
  • Chemistry, Medicine
  • Journal of the American Society for Mass Spectrometry
  • This paper reports a newly developed technique that uses artificial neural networks to aid in the automated interpretation of peptide sequence from high-energy collision-induced dissociation (CID) tandem mass spectra of peptides. Two artificial neural networks classify fragment ions before the commencement of an iterative sequencing algorithm. The first neural network provides an estimation of whether fragment ions belong to 1 of 11 specific categories, whereas the second network attempts to… CONTINUE READING
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    References

    SHOWING 1-10 OF 13 REFERENCES
    Pattern-based algorithm for peptide sequencing from tandem high energy collision-induced dissociation mass spectra
    • 62
    • PDF
    Computer program (SEQPEP) to aid in the interpretation of high-energy collision tandem mass spectra of peptides.
    • 112
    Amino acid sequence prerequisites for the formation of cn ions
    • 22
    • PDF
    Mass spectrometry of peptides and proteins.
    • K. Biemann
    • Chemistry, Medicine
    • Annual review of biochemistry
    • 1992
    • 311
    An introduction to computing with neural nets
    • 5,479
    Computer Software Applications in Chemistry
    • 61