Evidence map›Paper›PMID 24187339›Full record

ReviewMolecular & cellular proteomics : MCP2013

Status of large-scale analysis of post-translational modifications by mass spectrometry.

Jesper V Olsen, Matthias Mann

Abstract readReview
In one paragraph

Review in Molecular & cellular proteomics : MCP, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 280 papers.

0numbers the graph read from it
0cells of the map it votes in
280citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

280 citing papers in PubMed.

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  18. Computational Pipelines for Protein Ubiquitylation Analysis and Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  19. Review
  20. Article

220 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jesper V OlsenDepartment of Proteomics, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Blegdamsvej 3b, DK-2200 Copenhagen, Denmark;
Matthias Mann

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Protein Processing, Post-TranslationalSoftwareAcetylationComputational BiologyGene Expression RegulationGenome, HumanGlycosylationHumansMass SpectrometryMethylationPhosphorylationProteolysisUbiquitination

Identifiers

PMID24187339
PMCPMC3861698

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.