Evidence map›Paper›PMID 20127684›Full record

ArticleProteomics2010

Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps.

Ruth Isserlin, Daniele Merico, Rasoul Alikhani-Koupaei, Anthony Gramolini, Gary D Bader, Andrew Emili

Abstract read
In one paragraph

Article in Proteomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Proteomic Profiling Reveals Roles of Stress Response, CaAlcoholism, clinical and experimental research · 2020
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Proteomics for systems toxicology.Computational and structural biotechnology journal · 2014
    Review
  17. Article
  18. Review
  19. Article
  20. Systems proteomics for translational network medicine.Circulation. Cardiovascular genetics · 2012
    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

6 authors.

Ruth IsserlinBanting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.
Daniele Merico
Rasoul Alikhani-Koupaei
Anthony Gramolini
Gary D Bader
Andrew Emili

Funding

Pathway Commons: Research Resource for Biological PathwaysP41HG004118 · NHGRI · SLOAN-KETTERING INST CAN RESEARCH · PI SANDER, CHRIS · 2008 to 2011
$3.8M
CIHR 106538-1CIHR 87143-1NHGRI NIH HHS P41 HG004118NHGRI NIH HHS P41 P41HG04118
6 · The paper itself

Abstract

Global protein expression profiling can potentially uncover perturbations associated with common forms of heart disease. We have used shotgun MS/MS to monitor the state of biological systems in cardiac tissue correlating with disease onset, cardiac insufficiency and progression to heart failure in a time-course mouse model of dilated cardiomyopathy. However, interpreting the functional significance of the hundreds of differentially expressed proteins has been challenging. Here, we utilize improved enrichment statistical methods and an extensive collection of functionally related gene sets, gaining a more comprehensive understanding of the progressive alterations associated with functional decline in dilated cardiomyopathy. We visualize the enrichment results as an Enrichment Map, where significant gene sets are grouped based on annotation similarity. This approach vastly simplifies the interpretation of the large number of enriched gene sets found. For pathways of specific interest, such as Apoptosis and the MAPK (mitogen-activated protein kinase) cascade, we performed a more detailed analysis of the underlying signaling network, including experimental validation of expression patterns.

Indexed as

Gene Expression ProfilingAnimalsApoptosisCardiomyopathy, DilatedCaspase 3Databases, ProteinGelsolinMAP Kinase Signaling SystemMetabolomicsMicePropranololProteomicsSystems BiologyTandem Mass SpectrometryCaspase 3GelsolinPropranolol

Identifiers

PMID20127684
PMCPMC2879143

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.