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Informatics For Protein Identification by Tandem Mass Spectrometry; Focused on Two Most-widely Applied Algorithms, Mascot and SEQUEST
Chang Ho Sohn2, Jin Woo Jung1, Gum Yong Kang1 and Kwang Pyo Kim1,*
1Department of Molecular Biotechnology, Institute of Biomedical Science and Technology, Bio/Molecular Informatics Center, Konkuk University, Seoul 143-701, Korea
2Department of Chemistry, Seoul National University, Seoul 151-742, Korea
*Corresponding author
  Published : May 31, 2006
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Synopsis

Mass spectrometry(MS) is widely applied for high throughput proteomics analysis. When large-scale proteome analysis experiments are performed, it generates massive amount of data. To search these proteomics data against protein databases, fully automated database search algorithms, such as Mascot and SEQUEST are routinely employed. At present, it is critical to reduce false positives and false negatives during such analysis. In this review we have focused on aspects of automated protein identification using tandem mass spectrometry(MS/MS) spectra and validation of the protein identifications of two most common automated protein identification algorithms Mascot and SEQUEST.

Keyword: database searching, protein identification, proteomics, mass spectrometry
IBC   ISSN : 2005-8543   Contact IBC