• DocumentCode
    3317717
  • Title

    A New Scoring Scheme for Peptide Sequence Tagging via Doubly Charged MS/MS Spectra

  • Author

    Sun, Hanchang ; Zhang, Jiyang ; Liu, Hui ; Zhang, Wei ; Xu, Changming ; Wang, Tengjiao ; Xie, Hongwei

  • Author_Institution
    Coll. of Mechatron. & Autom., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2011
  • fDate
    10-12 May 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Peptide sequence tagging (PST) is one of the basic problems in computational proteomics. It is a flexible method which has been widely used in protein identification as well as mapping post-translational modifications (PTM) to peptides. In this work, we present a new scoring scheme for peptide sequence tagging via doubly charged tandem mass spectra. Four public datasets from different types of mass spectrometers (Thermo LTQ-FT, LTQ and LCQ, Waters/Micromass QTOF) are applied to test our scoring scheme and the results are compared with the widely used PST algorithm InsPecT. The results show that our method achieves higher accuracy and better performance than InsPecT. Based on the scoring scheme, we have developed a software tool named TVNovoTag, which is available at http://www.bprc.ac.cn/TVNovoTag/.
  • Keywords
    biology computing; identification technology; mass spectrometers; mass spectroscopy; proteomics; software tools; InsPecT; TVNovoTag; computational proteomics; doubly charged MS-MS spectra; doubly charged tandem mass spectra; mass spectrometers; peptide sequence tagging; post-translational modifications; protein identification; public datasets; software tool; Accuracy; Databases; Peptides; Proteins; Proteomics; Spectroscopy; Tagging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2151-7614
  • Print_ISBN
    978-1-4244-5088-6
  • Type

    conf

  • DOI
    10.1109/icbbe.2011.5780016
  • Filename
    5780016