Evidence map›Paper›PMID 22067443›Full record

ArticleNucleic acids research2012

PINA v2.0: mining interactome modules.

Mark J Cowley, Mark Pinese, Karin S Kassahn, Nic Waddell, John V Pearson, Sean M Grimmond, Andrew V Biankin, Sampsa Hautaniemi, Jianmin Wu

Abstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 197 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
197citing papers in PubMed, 3 pooled it
–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

197 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
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  7. The aging genome exhibits organized vulnerability to somatic mutations.bioRxiv : the preprint server for biology · 2026
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  16. Targeting DTX2/UFD1-mediated FTO degradation to regulate antitumor immunity.Proceedings of the National Academy of Sciences of the United States of America · 2024
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137 more citing papers are in PubMed but not listed here.

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

9 authors.

Mark J CowleyCancer Research Program, Peter Wills Bioinformatics Centre, Garvan Institute of Medical Research, Darlinghurst, Sydney, NSW 2010, Australia.
Mark Pinese
Karin S Kassahn
Nic Waddell
John V Pearson
Sean M Grimmond
Andrew V Biankin
Sampsa Hautaniemi
Jianmin Wu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Protein Interaction Network Analysis (PINA) platform is a comprehensive web resource, which includes a database of unified protein-protein interaction data integrated from six manually curated public databases, and a set of built-in tools for network construction, filtering, analysis and visualization. The second version of PINA enhances its utility for studies of protein interactions at a network level, by including multiple collections of interaction modules identified by different clustering approaches from the whole network of protein interactions ('interactome') for six model organisms. All identified modules are fully annotated by enriched Gene Ontology terms, KEGG pathways, Pfam domains and the chemical and genetic perturbations collection from MSigDB. Moreover, a new tool is provided for module enrichment analysis in addition to simple query function. The interactome data are also available on the web site for further bioinformatics analysis. PINA is freely accessible at http://cbg.garvan.unsw.edu.au/pina/.

Indexed as

Databases, ProteinProtein Interaction MappingAlgorithmsAnimalsCluster AnalysisComputer GraphicsData MiningHumansMiceMolecular Sequence AnnotationProteinsRatsSoftwareProteins

Identifiers

PMID22067443
PMCPMC3244997

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.