The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Status of Large-scale Analysis of Post-translational Modifications by Mass Spectrometry
Open accessAbstract
Cellular function can be controlled through the gene expression program, but often protein post-translational modifications (PTMs) provide a more precise and elegant mechanism. Key functional roles of specific modification events--for instance, during the cell cycle--have been known for decades, but only in the past 10 years has mass-spectrometry-(MS)-based proteomics begun to reveal the true extent of the PTM universe. In this overview for the special PTM issue of Molecular and Cellular Proteomics, we take stock of where MS-based proteomics stands in the large-scale analysis of protein modifications. For many PTMs, including phosphorylation, ubiquitination, glycosylation, and acetylation, tens of thousands of sites can now be confidently identified and localized in the sequence of the protein. The quantification of PTM levels between different cellular states is likewise established, with label-free methods showing particular promise. It is also becoming possible to determine the absolute occupancy or stoichiometry of PTM sites on a large scale. Powerful software for the bioinformatic analysis of thousands of PTM sites has been developed. However, a complete inventory of sites has not been established for any PTM, and this situation will persist into the foreseeable future. Furthermore, although PTM coverage by MS-based methods is impressive, it still needs to be improved, especially in tissues and in clinically relevant systems. The central challenge for the field is to develop streamlined methods for determining biological functions for the myriad of modifications now known to exist.
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
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
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
Self-citationRoss, 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
Blinded by the Light: The Growing Complexity of p53
Vousden, K. H., & Prives, C. (2009) · Cell · doi:10.1016/j.cell.2009.04.037 · Cited by 3,163
Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry
Syka, J. E. P., Coon, J. J., Schroeder, M. J., Shabanowitz, J., & Hunt, D. F. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0402700101 · Cited by 2,370
Tan, M., Luo, H., Lee, S., Jin, F., Yang, J. S., Montellier, E., Buchou, T., Cheng, Z., Rousseaux, S., Rajagopal, N., et al. (2011) · Cell · doi:10.1016/j.cell.2011.08.008 · Cited by 1,902
Identification of lysine succinylation as a new post-translational modification
Zhang, Z., Tan, M., Xie, Z., Dai, L., Chen, Y., & Zhao, Y. (2011) · Nature Chemical Biology · doi:10.1038/nchembio.495 · Cited by 1,027
Mapping intact protein isoforms in discovery mode using top-down proteomics
Tran, J. C., Zamdborg, L., Ahlf, D. R., Lee, J. E., Catherman, A. D., Durbin, K. R., Tipton, J. D., Vellaichamy, A., Kellie, J. F., Li, M., et al. (2011) · Nature · doi:10.1038/nature10575 · Cited by 665
Distinguishing protein-coding and noncoding genes in the human genome
Clamp, M., Fry, B., Kamal, M., Xie, X., Cuff, J., Lin, M. F., Kellis, M., Lindblad-Toh, K., & Lander, E. S. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709013104 · Cited by 624
Daub, H., Olsen, J. V., Bairlein, M., Gnad, F., Oppermann, F. S., Körner, R., Greff, Z., Kéri, G., Stemmann, O., & Mann, M. (2008) · Molecular Cell · doi:10.1016/j.molcel.2008.07.007 · Cited by 594
Self-citation
Cited by
Swatek, K. N., & Komander, D. (2016) · Cell Research · doi:10.1038/cr.2016.39 · Cited by 2,081
Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
Pejaver, V., Urresti, J., Lugo-Martinez, J., Pagel, K. A., Lin, G. N., Nam, H.-J., Mort, M., Cooper, D. N., Sebat, J., Iakoucheva, L. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19669-x · Cited by 923
The world of protein acetylation
Drazic, A., Myklebust, L. M., Ree, R., & Arnesen, T. (2016) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2016.06.007 · Cited by 804
A comprehensive compilation of SUMO proteomics
Hendriks, I. A., & Vertegaal, A. C. O. (2016) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.81 · Cited by 514
An Optimized Shotgun Strategy for the Rapid Generation of Comprehensive Human Proteomes
Bekker-Jensen, D. B., Kelstrup, C. D., Batth, T. S., Larsen, S. C., Haldrup, C., Bramsen, J. B., Sørensen, K. D., Høyer, S., Ørntoft, T. F., Andersen, C. L., et al. (2017) · Cell Systems · doi:10.1016/j.cels.2017.05.009 · Cited by 490
Self-citation
Metadata
- Authors
- Olsen, J. V., & Mann, M.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2013-12
- Volume
- 12
- Issue
- 12
- Pages
- 3444-3452
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2103174201
- Cited by
- 591
- References
- 13
- FWCI
- 26.84
- 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: Status of Large-scale Analysis of Post-translational Modifications by Mass Spectrometry. https://app.cochat.ai/papers/10.1074/mcp.o113.034181
- The paper
- Olsen, J. V., & Mann, M. (2013). Status of Large-scale Analysis of Post-translational Modifications by Mass Spectrometry. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.o113.034181
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.
