Evidence map›Paper›PMID 24702702›Full record

ReviewChemical reviews2014

Disordered proteinaceous machines.

Monika Fuxreiter, Ágnes Tóth-Petróczy, Daniel A Kraut, Andreas Matouschek, Andreas T Matouschek, Roderick Y H Lim, Bin Xue, Lukasz Kurgan, Vladimir N Uversky

Erratum issuedAbstract readReview
In one paragraph

Review in Chemical reviews, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing 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

62 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Prediction of Intrinsically Disordered Regions That Bind RNA with DisoRDPbind.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  6. SHARK-capture identifies functional motifs in intrinsically disordered protein regions.Protein science : a publication of the Protein Society · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. SHARK enables sensitive detection of evolutionary homologs and functional analogs in unalignable and disordered sequences.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Deep learning in prediction of intrinsic disorder in proteins.Computational and structural biotechnology journal · 2022
    Review
  20. Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Monika FuxreiterMTA-DE Momentum Laboratory of Protein Dynamics, Department of Biochemistry and Molecular Biology, University of Debrecen , Nagyerdei krt. 98, H-4032 Debrecen, Hungary.
Ágnes Tóth-Petróczy
Daniel A Kraut
Andreas Matouschek
Andreas T Matouschek
Roderick Y H Lim
Bin Xue
Lukasz Kurgan
Vladimir N Uversky

Funding

TRANS-NETWORK PROJECTSU54CA143869 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI O'HALLORAN, THOMAS V · 2009 to 2013
$12.8M
Interactions Regulating Translation and Protein Biogenesis in VivoU54GM105816 · NIGMS · UNIVERSITY OF NOTRE DAME · PI BUSKIRK, ALLEN ROWDON, CLARK, PATRICIA LOUISE · 2013 to 2017
$3.7M
Protein unfolding in a physiological systemR01GM063004 · NIGMS · NORTHWESTERN UNIVERSITY · PI MATOUSCHEK, ANDREAS · 2001 to 2012
$2.7M
NCI NIH HHS U54 CA143869NIGMS NIH HHS R01 GM063004NIGMS NIH HHS U54 GM105816NIGMS NIH HHS U54GM105816
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

HumansIntrinsically Disordered ProteinsNuclear Pore Complex ProteinsProtein UnfoldingRibonucleoproteinsIntrinsically Disordered ProteinsNuclear Pore Complex ProteinsRibonucleoproteins

Identifiers

PMID24702702
PMCPMC4350607

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.