Evidence map›Paper›PMID 22301388›Full record

ArticleMolecular & cellular proteomics : MCP2012

Analysis of high accuracy, quantitative proteomics data in the MaxQB database.

Christoph Schaab, Tamar Geiger, Gabriele Stoehr, Juergen Cox, Matthias Mann

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed, 1 pooled it
8.5field-weighted citation impact, top 1% of its field
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

98 citing papers in PubMed, 1 synthesis or guideline pooled it, 169 citations in OpenAlex.

  1. Integrating Multiple Quantitative Proteomic Analyses Using MetaMSD.Methods in molecular biology (Clifton, N.J.) · 2023
    Pooled it
  2. Gold micro-particles for knee osteoarthritis.European journal of pain (London, England) · 2022
    Trial
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  4. The Analysis ofCurrent issues in molecular biology · 2025
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  14. Proteome-wide Profiling of Asymmetric Dimethylated Arginine in Human Breast Tumors.Journal of the American Society for Mass Spectrometry · 2023
    Article
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  16. Review
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  18. Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review.International journal of chronic obstructive pulmonary disease · 2023
    Review
  19. Article
  20. Article

38 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

5 authors at 1 institution in 1 country.

Christoph SchaabDepartment of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, D-82152 Martinsried, Germany.
Tamar Geiger
Gabriele Stoehr
Juergen Cox
Matthias Mann
Max Planck Institute of Biochemistry · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MS-based proteomics generates rapidly increasing amounts of precise and quantitative information. Analysis of individual proteomic experiments has made great strides, but the crucial ability to compare and store information across different proteome measurements still presents many challenges. For example, it has been difficult to avoid contamination of databases with low quality peptide identifications, to control for the inflation in false positive identifications when combining data sets, and to integrate quantitative data. Although, for example, the contamination with low quality identifications has been addressed by joint analysis of deposited raw data in some public repositories, we reasoned that there should be a role for a database specifically designed for high resolution and quantitative data. Here we describe a novel database termed MaxQB that stores and displays collections of large proteomics projects and allows joint analysis and comparison. We demonstrate the analysis tools of MaxQB using proteome data of 11 different human cell lines and 28 mouse tissues. The database-wide false discovery rate is controlled by adjusting the project specific cutoff scores for the combined data sets. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted. We used MaxQB to calculate the signal reproducibility of the detected peptides for the same proteins across different proteomes. Spearman rank correlation between peptide intensity and detection probability of identified proteins was greater than 0.8 for 64% of the proteome, whereas a minority of proteins have negative correlation. This information can be used to pinpoint false protein identifications, independently of peptide database scores. The information contained in MaxQB, including high resolution fragment spectra, is accessible to the community via a user-friendly web interface at http://www.biochem.mpg.de/maxqb.

Indexed as

Databases, ProteinProteomicsSearch EngineAnimalsCells, CulturedChromatography, LiquidHumansMass SpectrometryMicePeptide FragmentsProteomeReproducibility of ResultsPeptide FragmentsProteome

Identifiers

PMID22301388
PMCPMC3316731
OpenAlexW2118001361

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.