Evidence map›Paper›PMID 25033288›Full record

ReviewBMC systems biology2014

Bioinformatic analysis of proteomics data.

Andreas Schmidt, Ignasi Forne, Axel Imhof

Abstract readReview
In one paragraph

Review in BMC systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 2 pooled it
–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

63 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Identification of Hip BMD Loss and Fracture Risk Markers Through Population-Based Serum Proteomics.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2017
    Trial
  4. Article
  5. Isolation and Characterization of 5-(1-Hydroxyethyl)-Dihydro-2-Furanone fromInternational journal of molecular sciences · 2026
    Article
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  9. Review
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  16. Article
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  18. Precision diagnostics in children.Cambridge prisms. Precision medicine · 2023
    Review
  19. Article
  20. Article

3 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

3 authors.

Andreas Schmidt
Ignasi Forne
Axel Imhof

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most biochemical reactions in a cell are regulated by highly specialized proteins, which are the prime mediators of the cellular phenotype. Therefore the identification, quantitation and characterization of all proteins in a cell are of utmost importance to understand the molecular processes that mediate cellular physiology. With the advent of robust and reliable mass spectrometers that are able to analyze complex protein mixtures within a reasonable timeframe, the systematic analysis of all proteins in a cell becomes feasible. Besides the ongoing improvements of analytical hardware, standardized methods to analyze and study all proteins have to be developed that allow the generation of testable new hypothesis based on the enormous pre-existing amount of biological information. Here we discuss current strategies on how to gather, filter and analyze proteomic data sates using available software packages.

Indexed as

Amino Acid MotifsAnimalsGene OntologyHumansProtein Interaction MappingProtein Structure, TertiaryProteomicsStatistics as Topic

Identifiers

PMID25033288
PMCPMC4108846

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.