MultiProtIdent Edit

Citations: 1

z-index: 0.08

Basic information
Short name MultiProtIdent
Full name
Description MultiProtIdent, which can identify proteins using additional information about protein-protein interactions and protein functional associations. Both single and multiple Peptide Mass Fingerprints (PMFs) are input to MultiProtIdent, which matches the PMFs to a theoretical peptide mass database.
URL http://dbms104.csie.ncu.edu.tw
Year founded 2005
Last update & version
Availability Not Available
Contact information
University/Institution hosted National Chiao-Tung University
Address Department of Biological Science and Technology and Institute of Bioinformatics, National Chiao-Tung University, Hsin-Chu 300, Taiwan
City Hsin-Chu
Province/State
Country/Region Taiwan, Province of China
Contact name Ann-Ping Tsou
Contact email
Data information
Data object
  • Animal
  • Plant
Data type
  • Protein
Database category
  • Interaction
Major organism
  • NA
Keyword
  • theoretical peptide mass
Publications
  • MultiProtIdent: identifying proteins using database search and protein-protein interactions. [PMID: 15952715]
    Hsien-Da Huang, Tzong-Yi Lee, Li-Cheng Wu, Feng-Mao Lin, Hsueh-Fen Juan, Jorng-Tzong Horng, Ann-Ping Tsou

    Protein identification is important in proteomics. Proteomic analyses based on mass spectra (MS) constitute innovative ways to identify the components of protein complexes. Instruments can obtain the mass spectrum to an accuracy of 0.01 Da or better, but identification errors are inevitable. This study shows a novel tool, MultiProtIdent, which can identify proteins using additional information about protein-protein interactions and protein functional associations. Both single and multiple Peptide Mass Fingerprints (PMFs) are input to MultiProtIdent, which matches the PMFs to a theoretical peptide mass database. The relationships or interactions among proteins are considered to reduce false positives in PMF matching. Experiments to identify protein complexes reveal that MultiProtIdent is highly promising. The website associated with this study is http://dbms104.csie.ncu.edu.tw/.

    J. Proteome Res. 2005:4(3)

    1 Citations (from Europe PMC, 2018-12-08)

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Record metadata

  • Created on: 2018-02-14
    • ***d@***c.cn [2018-03-08]
    • ***d@***c.cn [2018-03-07]

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