Encyclopedia of Algorithms

2008 Edition
| Editors: Ming-Yang Kao

Peptide De Novo Sequencing with MS/MS

2005; Ma, Zhang, Liang
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-30162-4_286

Keywords and Synonyms

De novo sequencing ; Peptide sequencing              

Problem Definition

De novosequencing arises from the identification of peptides by using tandem mass spectrometry (MS/MS). A peptide is a sequence of amino acids in biochemistry and can be regarded as a string over a finite alphabet from a computer scientist's point of view. Each letter in the alphabet represents a different kind of amino acid, and is associate with a mass value. In the biochemical experiment, a tandem mass spectrometer is utilized to fragment many copies of the peptide into pieces, and to measure the mass values (in fact, the mass to charge ratios) of the fragments simultaneously. This gives a tandem mass spectrum. Since different peptides normally produce different spectra, it is possible, and now a common practice, to deduce the amino acid sequence of the peptide from its spectrum. Often this deduction involves the searching in a database for a peptide that can possibly produce the...


Tandem Mass Tandem Mass Spectrometry Score Function Dynamic Programming Algorithm Mass Spectrum Tandem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Recommended Reading

  1. 1.
    Chen, T., Kao, M.-Y., Tepel, M., Rush J., Church, G.: A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry. J. Comput. Biol. 8(3), 325–337 (2001)CrossRefGoogle Scholar
  2. 2.
    Dančík, V., Addona, T., Clauser, K., Vath, J., Pevzner, P.: De novo protein sequencing via tandem mass-spectrometry. J. Comput. Biol. 6, 327–341 (1999)CrossRefGoogle Scholar
  3. 3.
    Fischer, B., Roth, V., Roos, F., Grossmann, J., Baginsky, S., Widmayer, P., Gruissem, W., Buhmann J.: NovoHMM: A Hidden Markov Model for de novo peptide sequencing. Anal. Chem. 77, 7265–7273 (2005)CrossRefGoogle Scholar
  4. 4.
    Frank, A., Pevzner, P.: Pepnovo: De novo peptide sequencing via probabilistic network modeling. Anal. Chem. 77, 964–973 (2005)CrossRefGoogle Scholar
  5. 5.
    Ma, B., Zhang, K., Liang, C.: An effective algorithm for the peptide de novo sequencing from MS/MS spectrum. J. Comput. Syst. Sci. 70, 418–430 (2005)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Ma, B., Zhang, K., Lajoie, G., Doherty-Kirby, A., Hendrie, C., Liang, C., Li, M.: PEAKS: Powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun. Mass Spectrom. 17(20), 2337–2342 (2003)CrossRefGoogle Scholar
  7. 7.
    Pevtsov, S., Fedulova, I., Mirzaei, H., Buck, C., Zhang, X.: Performance evaluation of existing de novo sequencing algorithms. J. Proteome Res. 5(11), 3018–3028 (2006) ASAP Article 10.1021/pr060222hCrossRefGoogle Scholar
  8. 8.
    Steen, H., Mann, M.: The ABC's (and XYZ's) of peptide sequencing. Nat. Rev. Mol. Cell Biol. 5(9), 699–711 (2004)CrossRefGoogle Scholar
  9. 9.
    Xu, C., Ma, B.: Software for Computational Peptide Identification from MS/MS. Drug Discov. Today 11(13/14), 595–600 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Bin Ma
    • 1
  1. 1.Department of Computer ScienceUniversity of Western OntarioLondonCanada