Evidence map›Paper›PMID 18211718›Full record

ArticleGenome biology2008

Towards defining the nuclear proteome.

J Lynn Fink, Seetha Karunaratne, Amit Mittal, Donald M Gardiner, Nicholas Hamilton, Donna Mahony, Chikatoshi Kai, Harukazu Suzuki, Yosihide Hayashizaki, Rohan D Teasdale

Abstract read
In one paragraph

Article in Genome biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Trial
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  3. Review
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  5. Article
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  11. NSort/DB: an intranuclear compartment protein database.Genomics, proteomics & bioinformatics · 2012
    Article
  12. Sorting the nuclear proteome.Bioinformatics (Oxford, England) · 2011
    Article
  13. A probabilistic model of nuclear import of proteins.Bioinformatics (Oxford, England) · 2011
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
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

10 authors.

J Lynn FinkARC Centre of Excellence in Bioinformatics, The University of Queensland, St Lucia, Queensland, 4072, Australia.
Seetha Karunaratne
Amit Mittal
Donald M Gardiner
Nicholas Hamilton
Donna Mahony
Chikatoshi Kai
Harukazu Suzuki
Yosihide Hayashizaki
Rohan D Teasdale

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe nucleus is a complex cellular organelle and accurately defining its protein content is essential before any systematic characterization can be considered.

resultsWe report direct evidence for 2,568 mammalian proteins within the nuclear proteome: the nuclear subcellular localization of 1,529 proteins based on a high-throughput subcellular localization protocol of full-length proteins and an additional 1,039 proteins for which clear experimental evidence is documented in published literature. This is direct evidence that the nuclear proteome consists of at least 14% of the entire proteome. This dataset was used to evaluate computational approaches designed to identify additional nuclear proteins.

conclusionThis represents direct experimental evidence that the nuclear proteome consists of at least 14% of the entire proteome. This high-quality nuclear proteome dataset was used to evaluate computational approaches designed to identify additional nuclear proteins. Based on this analysis, researchers can determine the stringency and types of lines of evidence they consider to infer the size and complement of the nuclear proteome.

Indexed as

ProteomeAnimalsCell NucleusComputational BiologyHumansNuclear ProteinsNuclear ProteinsProteome

Identifiers

PMID18211718
PMCPMC2395251

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.