Abstract
Proteomics is a still-evolving combination of technologies to describe and characterize all expressed proteins in a biological system. Because of upper limits on mass detection of mass spectrometers, the bottom-up approach is most widely employed in which tryptic peptides are quantified and identified from complex protein mixtures. Protein identification from tandem mass spectra is still a challenge in proteomics. Two approaches have been developed to identify proteins from tandem mass spectra, database searching and de novo sequencing. These approaches typically have positive identification rates of only ∼10-20%, and exhibit high false positive identification rates. This review surveys existing algorithms developed for database searching and de novo sequencing, with a focus on recent developments for tandem mass spectrum quality assessment, peptide identification using annotated spectra libraries, statistical approaches to assess identification quality, and methods for constrained searches. We also review research comparing the performance of existing protein identification packages.
Keywords: Protein identification, mass spectrometry, database searching, de novo sequencing, data preprocessing, intensity based identification
Current Proteomics
Title: Current Status of Computational Approaches for Protein Identification Using Tandem Mass Spectra
Volume: 4 Issue: 3
Author(s): Xiang Zhang, Cheolhwan Oh, Catherine P. Riley and Charles Buck
Affiliation:
Keywords: Protein identification, mass spectrometry, database searching, de novo sequencing, data preprocessing, intensity based identification
Abstract: Proteomics is a still-evolving combination of technologies to describe and characterize all expressed proteins in a biological system. Because of upper limits on mass detection of mass spectrometers, the bottom-up approach is most widely employed in which tryptic peptides are quantified and identified from complex protein mixtures. Protein identification from tandem mass spectra is still a challenge in proteomics. Two approaches have been developed to identify proteins from tandem mass spectra, database searching and de novo sequencing. These approaches typically have positive identification rates of only ∼10-20%, and exhibit high false positive identification rates. This review surveys existing algorithms developed for database searching and de novo sequencing, with a focus on recent developments for tandem mass spectrum quality assessment, peptide identification using annotated spectra libraries, statistical approaches to assess identification quality, and methods for constrained searches. We also review research comparing the performance of existing protein identification packages.
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Cite this article as:
Zhang Xiang, Oh Cheolhwan, Riley P. Catherine and Buck Charles, Current Status of Computational Approaches for Protein Identification Using Tandem Mass Spectra, Current Proteomics 2007; 4 (3) . https://dx.doi.org/10.2174/157016407783221349
DOI https://dx.doi.org/10.2174/157016407783221349 |
Print ISSN 1570-1646 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6247 |
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Mass spectrometry data acquisition and analysis for proteomics
The Thematic Issue on "Mass spectrometry data acquisition and analysis for proteomics" aims to explore the latest advancements and challenges in the field of proteomics through the lens of mass spectrometry. Proteomics, the large-scale study of proteins and their functions, plays a crucial role in understanding various biological processes and ...read more
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The Editors of the Current Proteomics (CP) journal are highly privileged to welcome scientists to submit their scientific research and review articles to be considered for publication in the upcoming thematic issue. The topics should cover various aspects of peptides in regard to their synthetic methodologies, formulation approaches, pharmacological challenges, ...read more
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