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Cited by 225

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Tools for Label-free Peptide Quantification

Open access
Nahnsen, Sven, Bielow, Chris, Reinert, Knut, Kohlbacher, Oliver·2013·Molecular & Cellular Proteomics
DOI 10.1074/mcp.r112.025163
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Abstract

The increasing scale and complexity of quantitative proteomics studies complicate subsequent analysis of the acquired data. Untargeted label-free quantification, based either on feature intensities or on spectral counting, is a method that scales particularly well with respect to the number of samples. It is thus an excellent alternative to labeling techniques. In order to profit from this scalability, however, data analysis has to cope with large amounts of data, process them automatically, and do a thorough statistical analysis in order to achieve reliable results. We review the state of the art with respect to computational tools for label-free quantification in untargeted proteomics. The two fundamental approaches are feature-based quantification, relying on the summed-up mass spectrometric intensity of peptides, and spectral counting, which relies on the number of MS/MS spectra acquired for a certain protein. We review the current algorithmic approaches underlying some widely used software packages and briefly discuss the statistical strategies for analyzing the data.

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Metadata

Authors
Nahnsen, S., Bielow, C., Reinert, K., & Kohlbacher, O.
Venue
Molecular & Cellular Proteomics
Publisher
Elsevier BV
Published
2013-03
Volume
12
Issue
3
Pages
549-556
ISSN
1535-9476 (ISSN-L)
DOI
10.1074/mcp.r112.025163
OpenAlex
W2162128341
Cited by
225
References
11
FWCI
9.84
Type
journal article
Language
en
Open access
hybrid
Licence

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CoChat. (2026). Citation check: Tools for Label-free Peptide Quantification. https://app.cochat.ai/papers/10.1074/mcp.r112.025163
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Nahnsen, S., Bielow, C., Reinert, K., & Kohlbacher, O. (2013). Tools for Label-free Peptide Quantification. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.r112.025163

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