The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Isobaric Labeling-Based Relative Quantification in Shotgun Proteomics
Open accessAbstract
Mass spectrometry plays a key role in relative quantitative comparisons of proteins in order to understand their functional role in biological systems upon perturbation. In this review, we review studies that examine different aspects of isobaric labeling-based relative quantification for shotgun proteomic analysis. In particular, we focus on different types of isobaric reagents and their reaction chemistry (e.g., amine-, carbonyl-, and sulfhydryl-reactive). Various factors, such as ratio compression, reporter ion dynamic range, and others, cause an underestimation of changes in relative abundance of proteins across samples, undermining the ability of the isobaric labeling approach to be truly quantitative. These factors that affect quantification and the suggested combinations of experimental design and optimal data acquisition methods to increase the precision and accuracy of the measurements will be discussed. Finally, the extended application of isobaric labeling-based approach in hyperplexing strategy, targeted quantification, and phosphopeptide analysis are also examined.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., et al. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400129-mcp200 · Cited by 4,401
McAlister, G. C., Nusinow, D. P., Jedrychowski, M. P., Wühr, M., Huttlin, E. L., Erickson, B. K., Rad, R., Haas, W., & Gygi, S. P. (2014) · Analytical Chemistry · doi:10.1021/ac502040v · Cited by 1,263
MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics
Ting, L., Rad, R., Gygi, S. P., & Haas, W. (2011) · Nature Methods · doi:10.1038/nmeth.1714 · Cited by 1,009
Increasing the Multiplexing Capacity of TMTs Using Reporter Ion Isotopologues with Isobaric Masses
McAlister, G. C., Huttlin, E. L., Haas, W., Ting, L., Jedrychowski, M. P., Rogers, J. C., Kuhn, K., Pike, I., Grothe, R. A., Blethrow, J. D., et al. (2012) · Analytical Chemistry · doi:10.1021/ac301572t · Cited by 605
Cited by
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Ping, L., Zhou, M., Yin, L., Higginbotham, L. A., Guajardo, A., White, B., Troncoso, J. C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0815-6 · Cited by 1,001
Lenalidomide induces ubiquitination and degradation of CK1α in del(5q) MDS
Krönke, J., Fink, E. C., Hollenbach, P. W., MacBeth, K. J., Hurst, S. N., Udeshi, N. D., Chamberlain, P. P., Mani, D. R., Man, H. W., Gandhi, A. K., et al. (2015) · Nature · doi:10.1038/nature14610 · Cited by 863
Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma
Clark, D. J., Dhanasekaran, S. M., Petralia, F., Pan, J., Song, X., Hu, Y., da Veiga Leprevost, F., Reva, B., Lih, T.-S. M., Chang, H.-Y., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.007 · Cited by 730
Johnson, E. C. B., Carter, E. K., Dammer, E. B., Duong, D. M., Gerasimov, E. S., Liu, Y., Liu, J., Betarbet, R., Ping, L., Yin, L., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-021-00999-y · Cited by 561
Higginbotham, L., Ping, L., Dammer, E. B., Duong, D. M., Zhou, M., Gearing, M., Hurst, C., Glass, J. D., Factor, S. A., Johnson, E. C. B., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz9360 · Cited by 367
Metadata
- Authors
- Rauniyar, N., & Yates, J. R.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-11-04
- Volume
- 13
- Issue
- 12
- Pages
- 5293-5309
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2436016506
- Cited by
- 596
- References
- 6
- FWCI
- 14.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Isobaric Labeling-Based Relative Quantification in Shotgun Proteomics. https://app.cochat.ai/papers/10.1021/pr500880b
- The paper
- Rauniyar, N., & Yates, J. R. (2014). Isobaric Labeling-Based Relative Quantification in Shotgun Proteomics. Journal of Proteome Research. https://doi.org/10.1021/pr500880b
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
