The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A label‐free quantification method by MS/MS TIC compared to SILAC and spectral counting in a proteomics screen
Open accessAbstract
In order to assess the biological function of proteins and their modifications for understanding signaling mechanisms within cells as well as specific biomarkers to disease, it is important that quantitative information be obtained under different experimental conditions. Stable isotope labeling is a powerful method for accurately determining changes in the levels of proteins and PTMs; however, isotope labeling experiments suffer from limited dynamic range resulting in signal change ratios of less than ∼20:1 using most commercial mass spectrometers. Label‐free approaches to relative quantification in proteomics such as spectral counting have gained popularity since no additional chemistries are needed. Here, we show a label‐free method for relative quantification based on the TIC from peptide MS/MS spectra collected from data‐dependent runs can be used effectively as a quantitative measure and expands the dynamic range over isotope labeling experiments allowing for abundance differences up to ∼60:1 in a screen for proteins that bind to phosphotyrosine residues.
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
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
Functional and quantitative proteomics using SILAC
Mann, M. (2006) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2067 · Cited by 931
Cited by
Protein Analysis by Shotgun/Bottom-up Proteomics
Zhang, Y., Fonslow, B. R., Shan, B., Baek, M.-C., & Yates, J. R. (2013) · Chemical Reviews · doi:10.1021/cr3003533 · Cited by 1,491
Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present
Bantscheff, M., Lemeer, S., Savitski, M. M., & Kuster, B. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-6203-4 · Cited by 801
Mass Spectrometry-Based Label-Free Quantitative Proteomics
Zhu, W., Smith, J. W., & Huang, C.-M. (2010) · Journal of Biomedicine and Biotechnology · doi:10.1155/2010/840518 · Cited by 629
CasX enzymes comprise a distinct family of RNA-guided genome editors
Liu, J.-J., Orlova, N., Oakes, B. L., Ma, E., Spinner, H. B., Baney, K. L. M., Chuck, J., Tan, D., Knott, G. J., Harrington, L. B., et al. (2019) · Nature · doi:10.1038/s41586-019-0908-x · Cited by 446
Role of spectral counting in quantitative proteomics
Lundgren, D. H., Hwang, S.-I., Wu, L., & Han, D. K. (2010) · Expert Review of Proteomics · doi:10.1586/epr.09.69 · Cited by 428
Metadata
- Authors
- Asara, J. M., Christofk, H. R., Freimark, L. M., & Cantley, L. C.
- Venue
- PROTEOMICS
- Publisher
- Wiley
- Published
- 2008-03
- Volume
- 8
- Issue
- 5
- Pages
- 994-999
- ISSN
- 1615-9853 (ISSN-L)
- 1615-9861
- OpenAlex
- W2147246316
- Cited by
- 218
- References
- 2
- FWCI
- 8.02
- Type
- journal article
- Language
- en
- Open access
- bronze
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: A label‐free quantification method by MS/MS TIC compared to SILAC and spectral counting in a proteomics screen. https://app.cochat.ai/papers/10.1002/pmic.200700426
- The paper
- Asara, J. M., Christofk, H. R., Freimark, L. M., & Cantley, L. C. (2008). A label‐free quantification method by MS/MS TIC compared to SILAC and spectral counting in a proteomics screen. PROTEOMICS. https://doi.org/10.1002/pmic.200700426
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.
