The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Correlation Algorithm for the Automated Quantitative Analysis of Shotgun Proteomics Data
Abstract
Quantitative shotgun proteomic analyses are facilitated using chemical tags such as ICAT and metabolic labeling strategies with stable isotopes. The rapid high-throughput production of quantitative "shotgun" proteomic data necessitates the development of software to automatically convert mass spectrometry-derived data of peptides into relative protein abundances. We describe a computer program called RelEx, which uses a least-squares regression for the calculation of the peptide ion current ratios from the mass spectrometry-derived ion chromatograms. RelEx is tolerant of poor signal-to-noise data and can automatically discard nonusable chromatograms and outlier ratios. We apply a simple correction for systematic errors that improves the accuracy of the quantitative measurement by 32 +/- 4%. Our automated approach was validated using labeled mixtures composed of known molar ratios and demonstrated in a real sample by measuring the effect of osmotic stress on protein expression in Saccharomyces cerevisiae.
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Cites
Smoothing and Differentiation of Data by Simplified Least Squares Procedures.
Savitzky, A., & Golay, M. J. E. (1964) · Analytical Chemistry · doi:10.1021/ac60214a047 · Cited by 21,904
Microarray data normalization and transformation
Quackenbush, J. (2002) · Nature Genetics · doi:10.1038/ng1032 · Cited by 1,975
Cited by
Ishihama, Y., Oda, Y., Tabata, T., Sato, T., Nagasu, T., Rappsilber, J., & Mann, M. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500061-mcp200 · Cited by 2,055
Mass spectrometry–based proteomics turns quantitative
Ong, S.-E., & Mann, M. (2005) · Nature Chemical Biology · doi:10.1038/nchembio736 · Cited by 1,572
Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics
Old, W. M., Meyer-Arendt, K., Aveline-Wolf, L., Pierce, K. G., Mendoza, A., Sevinsky, J. R., Resing, K. A., & Ahn, N. G. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500084-mcp200 · Cited by 1,206
Proteomics by Mass Spectrometry: Approaches, Advances, and Applications
Yates, J. R., Ruse, C. I., & Nakorchevsky, A. (2009) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-061008-124934 · Cited by 1,078
Self-citationInterpretation of Shotgun Proteomic Data
Nesvizhskii, A. I., & Aebersold, R. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r500012-mcp200 · Cited by 1,025
Metadata
- Authors
- MacCoss, M. J., Wu, C. C., Liu, H., Sadygov, R., & Yates, J. R.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2003-11-06
- Volume
- 75
- Issue
- 24
- Pages
- 6912-6921
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2068523567
- Cited by
- 278
- References
- 2
- FWCI
- 8.93
- Type
- journal article
- Language
- en
- Open access
- closed
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- MacCoss, M. J., Wu, C. C., Liu, H., Sadygov, R., & Yates, J. R. (2003). A Correlation Algorithm for the Automated Quantitative Analysis of Shotgun Proteomics Data. Analytical Chemistry. https://doi.org/10.1021/ac034790h
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