Evidence map›Paper›PMID 30137231›Full record

ArticleBioinformatics (Oxford, England)2019

Increased sensitivity with automated validation of XL-MS cleavable peptide crosslinks.

Andrew Keller, Juan D Chavez, James E Bruce

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Intra-organ cell specific mitochondrial quantitative interactomics.bioRxiv : the preprint server for biology · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Tools for 3D Interactome Visualization.Journal of proteome research · 2019
    Article
  17. 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

3 authors.

Andrew KellerDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Juan D ChavezDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
James E BruceDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.

Funding

Protein Interaction Technology CoreU19AI107775 · NIAID · UNIVERSITY OF WASHINGTON · PI BRITTNACHER, MITCHELL J · 2013 to 2017
$7.7M
Quantitation of protein interactions in cancer cellsR01GM086688 · NIGMS · UNIVERSITY OF WASHINGTON · PI BRUCE, JAMES EDWARD · 2009 to 2019
$4.2M
NIAID NIH HHS U19 AI107775NIGMS NIH HHS R01 GM086688
6 · The paper itself

Abstract

motivationPeptides crosslinked with cleavable chemical crosslinkers are identified with mass spectrometry by independent database search of spectra associated with the two linked peptides. A major challenge is to combine together the evidence of the two peptides into an overall assessment of the two-peptide crosslink.

resultsHere, we describe software that models crosslink specific information to automatically validate XL-MS cleavable peptide crosslinks. Using a dataset of crosslinked protein mixtures, we demonstrate that it computes accurate and highly discriminating probabilities, enabling as many as 75% more identifications than was previously possible using only search scores and a predictable false discovery rate. AVAILABILITY AND IMPLEMENTATION: XLinkProphet software is freely available on the web at http://brucelab.gs.washington.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Databases, ProteinAlgorithmsAutomationMass SpectrometryPeptidesProteinsSoftwarePeptidesProteins

Identifiers

PMID30137231
PMCPMC6394394

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.