• DocumentCode
    2463021
  • Title

    Protein Sequencing with an Adaptive Genetic Algorithm from Tandem Mass Spectrometry

  • Author

    Boisson, Jean-Charles ; Jourdan, Laetitia ; Talbi, El-Ghazali ; Rolando, Christian

  • Author_Institution
    LIFL/INRIA Futurs., Villeneuve d´´Ascq
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1412
  • Lastpage
    1419
  • Abstract
    In Proteomics, only the de novo peptide sequencing approach allows a partial amino acid sequence of a peptide to be found from a MS/MS spectrum. In this article a preliminary work is presented to discover a complete protein sequence from spectral data (MS and MS/MS spectra). For the moment, our approach only uses MS spectra. A genetic algorithm (GA) has been designed with a new evaluation function which works directly with a complete MS spectrum as input and not with a mass list like the other methods using this kind of data. Thus the mono isotopic peak extraction step which needs a human intervention is deleted. The goal of this approach is to discover the sequence of unknown proteins and to allow a better understanding of the differences between experimental proteins and proteins from databases.
  • Keywords
    genetic algorithms; mass spectra; proteins; adaptive genetic algorithm; amino acid; de novo peptide sequencing; protein sequencing; proteomics; tandem mass spectrometry; Algorithm design and analysis; Amino acids; Data mining; Genetic algorithms; Humans; MONOS devices; Mass spectroscopy; Peptides; Protein sequence; Proteomics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9487-9
  • Type

    conf

  • DOI
    10.1109/CEC.2006.1688474
  • Filename
    1688474