Evidence map›Paper›PMID 28981707›Full record

ArticleNucleic acids research2018

The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics.

Alejandro Brenes, Vackar Afzal, Robert Kent, Angus I Lamond

Abstract readDataset
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Novel biochemical, structural, and systems insights into inflammatory signaling revealed by contextual interaction proteomics.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. The Encyclopedia of Proteome Dynamics: the KinoViewer.Bioinformatics (Oxford, England) · 2019
    Article
  11. Article
  12. Article
  13. 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

4 authors.

Alejandro BrenesCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK.
Vackar AfzalCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK.
Robert KentCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK.
Angus I LamondCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee DD1 5EH, UK.

Funding

Wellcome Trust 073980/Z/03/ZWellcome Trust 098503/E/12/ZWellcome Trust 105024/Z/14/Z
6 · The paper itself

Abstract

Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS files and processed peptide and protein identifications. MS-based proteomics technology is also used increasingly to measure additional protein properties affecting cellular function and disease mechanisms, including post-translational modifications, protein-protein interactions, subcellular and tissue distributions. Consequently, biologists and clinicians need innovative tools to conveniently analyse, visualize and explore such large, complex proteomics data and to integrate it with genomics and other related large-scale datasets. We have created the Encyclopedia of Proteome Dynamics (EPD) to meet this need (https://peptracker.com/epd/). The EPD combines a polyglot persistent database and web-application that provides open access to integrated proteomics data for >30 000 proteins from published studies on human cells and model organisms. It is designed to provide a user-friendly interface, featuring graphical navigation with interactive visualizations that facilitate powerful data exploration in an intuitive manner. The EPD offers a flexible and scalable ecosystem to integrate proteomics data with genomics information, RNA expression and other related, large-scale datasets.

Indexed as

Databases, FactualProteomeAnimalsBig DataData DisplayHumansInternetMass SpectrometryProteomicsUser-Computer InterfaceProteome

Identifiers

PMID28981707
PMCPMC5753345

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.