Evidence map›Paper›PMID 25978996›Full record

ArticleNature chemical biology2015

Application guide for omics approaches to cell signaling.

Zhong Yao, Julia Petschnigg, Robin Ketteler, Igor Stagljar

Abstract read
PubMed Publisher
In one paragraph

Article in Nature chemical biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Editorial: Multi-Omics Approaches to Study Signaling Pathways.Frontiers in bioengineering and biotechnology · 2020
    Article
  12. Article
  13. Towards a data-integrated cell.Nature communications · 2019
    Article
  14. FRETting about the affinity of bimolecular protein-protein interactions.Protein science : a publication of the Protein Society · 2018
    Article
  15. Article
  16. Food safety (Tokyo, Japan) · 2018
    Review
  17. Article
  18. Article
  19. Article
  20. 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

4 authors.

Zhong YaoDonnelly Centre, University of Toronto, Toronto, Ontario, Canada.
Julia PetschniggMRC Laboratory for Molecular Cell Biology, University College London, London, UK.
Robin KettelerMRC Laboratory for Molecular Cell Biology, University College London, London, UK.
Igor Stagljar1] Donnelly Centre, University of Toronto, Toronto, Ontario, Canada. [2] Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada. [3] Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.

Funding

Biotechnology and Biological Sciences Research Council BB/JO/5581/1Medical Research Council MC_EX_G0800785
6 · The paper itself

Abstract

Research in signal transduction aims to identify the functions of different signaling pathways in physiological and pathological states. Traditional techniques using biochemical, genetic or cell biological approaches have made important contributions to our understanding of cellular signaling. However, the single-gene approach does not take into account the full complexity of cell signaling. With the availability of omics techniques, great progress has been made in understanding signaling networks. Omics approaches can be classified into two categories: 'molecular profiling', including genomic, proteomic, post-translational modification and interactome profiling; and 'molecular perturbation', including genetic and functional perturbations.

Indexed as

Signal TransductionBiomedical ResearchProtein Array AnalysisProteomeProteomicsProteome

Identifiers

PMID25978996

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.