Abstract
Bottom-up proteomics (mass spectrometry analysis of peptides obtained by proteolysis and separated by liquid chromatography, (LC-MS/MS)) is one of the most frequently used techniques for identifying and characterizing proteins in biological samples. A key element of the analysis is database searching when the mass spectra of the peptides are compared with a database of theoretically computed (or experimental) peptide spectra. Here we discuss the main computational approaches to spectrum database searching and the statistical analysis of the results.
Keywords: Database search, Mass spectrometry, Protein identification, Proteomics, mass spectrum, Liquid chromatography, pattern recognition, genome annotation, 3D structure analysis), fragment
Current Bioinformatics
Title:Database Searching in Mass Spectrometry Based Proteomics
Volume: 7 Issue: 2
Author(s): Attila Kertesz-Farkas, Beata Reiz, Michael P. Myers and Sandor Pongor
Affiliation:
Keywords: Database search, Mass spectrometry, Protein identification, Proteomics, mass spectrum, Liquid chromatography, pattern recognition, genome annotation, 3D structure analysis), fragment
Abstract: Bottom-up proteomics (mass spectrometry analysis of peptides obtained by proteolysis and separated by liquid chromatography, (LC-MS/MS)) is one of the most frequently used techniques for identifying and characterizing proteins in biological samples. A key element of the analysis is database searching when the mass spectra of the peptides are compared with a database of theoretically computed (or experimental) peptide spectra. Here we discuss the main computational approaches to spectrum database searching and the statistical analysis of the results.
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Cite this article as:
Kertesz-Farkas Attila, Reiz Beata, P. Myers Michael and Pongor Sandor, Database Searching in Mass Spectrometry Based Proteomics, Current Bioinformatics 2012; 7 (2) . https://dx.doi.org/10.2174/157489312800604354
DOI https://dx.doi.org/10.2174/157489312800604354 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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