Evidence map›Paper›PMID 30520642›Full record

ArticleJournal of proteome research2019

Tools for 3D Interactome Visualization.

Andrew Keller, Juan D Chavez, Jimmy K Eng, Zorian Thornton, James E Bruce

Abstract read
In one paragraph

Article in Journal of proteome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Intra-organ cell specific mitochondrial quantitative interactomics.bioRxiv : the preprint server for biology · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Mitochondrial protein interaction landscape of SS-31.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  19. Article
  20. Article
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.

Andrew KellerDepartment of Genome Sciences , University of Washington , Seattle , Washington 98195 , United States.
Juan D ChavezDepartment of Genome Sciences , University of Washington , Seattle , Washington 98195 , United States.
Jimmy K EngDepartment of Genome Sciences , University of Washington , Seattle , Washington 98195 , United States.
Zorian ThorntonDepartment of Genome Sciences , University of Washington , Seattle , Washington 98195 , United States.
James E BruceDepartment of Genome Sciences , University of Washington , Seattle , Washington 98195 , United States.ORCID 0000-0001-6441-6089

Funding

Protein Interaction Technology CoreU19AI107775 · NIAID · UNIVERSITY OF WASHINGTON · PI MILLER, SAMUEL I · 2013 to 2017
$7.7M
NAD+/NADH ratio, protein acetylation and mitochondrial functionR01HL110349 · NHLBI · UNIVERSITY OF WASHINGTON · PI TIAN, RONG · 2011 to 2020
$5.7M
Quantitation of protein interactions in cancer cellsR01GM086688 · NIGMS · UNIVERSITY OF WASHINGTON · PI BRUCE, JAMES EDWARD · 2009 to 2019
$4.2M
Mitochondrial function and glycolytic switch in pathological cardiac hypertrophyR01HL142628 · NHLBI · UNIVERSITY OF WASHINGTON · PI TIAN, RONG · 2018 to 2021
$2.4M
NHLBI NIH HHS R01 HL110349NHLBI NIH HHS R01 HL142628NIAID NIH HHS U19 AI107775NIGMS NIH HHS R01 GM086688
6 · The paper itself

Abstract

In cells, intra- and intermolecular interactions of proteins confer function, and the dynamic modulation of this interactome is critical to meet the changing needs required to support life. Cross-linking and mass spectrometry (XL-MS) enable the detection of both intra- and intermolecular protein interactions in organelles, cells, tissues, and organs. Quantitative XL-MS enables the detection of interactome changes in cells due to environmental, phenotypic, pharmacological, or genetic perturbations. We have developed new informatics capabilities, the first to enable 3D visualization of multiple quantitative interactome data sets, acquired over time or with varied perturbation levels, to reveal relevant dynamic interactome changes. These new tools are integrated within release 3.0 of our online cross-linked peptide database and analysis tool suite XLinkDB. With the recent rapid expansion in XL-MS for protein structural studies and the extension to quantitative XL-MS measurements, 3D interactome visualization tools are of critical need.

Indexed as

SoftwareComputational BiologyHumansModels, MolecularProtein ConformationProtein Interaction MappingProteinsProteomicsProteinscross-link databasecross-linkingdynamic interactomeheatmapinteraction surfacesinteractome moviesmass spectrometryprotein complexesprotein interaction networksquantitative proteomics

Identifiers

PMID30520642
PMCPMC6519740

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.