Evidence map›Paper›PMID 24036287›Full record

ReviewPain2013

PainNetworks: a web-based resource for the visualisation of pain-related genes in the context of their network associations.

James R Perkins, Jonathan Lees, Ana Antunes-Martins, Ilhem Diboun, Stephen B McMahon, David L H Bennett, Christine Orengo

Open access · greenAbstract readReview
In one paragraph

Review in Pain, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 10% of its field
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

James R PerkinsInstitute of Structural and Molecular Biology, University College London, London, UK The Wolfson Centre for Age-Related Diseases, King's College London, Guy's Campus, London, UK The Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK Department of physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City, Doha, P.O. Box 24144, Qatar.
Jonathan Lees
Ana Antunes-Martins
Ilhem Diboun
Stephen B McMahon
David L H Bennett
Christine Orengo
Institute of Structural and Molecular Biology · GBKing's College London · GBJohn Radcliffe Hospital · GB

Funding

Wellcome Trust 095698
6 · The paper itself

Abstract

Hundreds of genes are proposed to contribute to nociception and pain perception. Historically, most studies of pain-related genes have examined them in isolation or alongside a handful of other genes. More recently the use of systems biology techniques has enabled us to study genes in the context of the biological pathways and networks in which they operate. Here we describe a Web-based resource, available at http://www.PainNetworks.org. It integrates interaction data from various public databases with information on known pain genes taken from several sources (eg, The Pain Genes Database) and allows the user to examine a gene (or set of genes) of interest alongside known interaction partners. This information is displayed by the resource in the form of a network. The user can enrich these networks by using data from pain-focused gene expression studies to highlight genes that change expression in a given experiment or pairs of genes showing correlated expression patterns across different experiments. Genes in the networks are annotated in several ways including biological function and drug binding. The Web site can be used to find out more about a gene of interest by looking at the function of its interaction partners. It can also be used to interpret the results of a functional genomics experiment by revealing putative novel pain-related genes that have similar expression patterns to known pain-related genes and by ranking genes according to their network connections with known pain genes. We expect this resource to grow over time and become a valuable asset to the pain community.

Indexed as

User-Computer InterfaceAnimalsGene Regulatory NetworksHumansInternetPainProtein Interaction MapsMicroarraysPain genesProtein interaction networkProtein–protein interactionsSystems biologyWeb-based resource

Identifiers

PMID24036287
PMCPMC3863956
OpenAlexW2028525915

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.