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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

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. 

Original languageEnglish
Pages (from-to)2586e1–2586e12
Number of pages12
JournalPain
Volume154
Issue number12
DOIs
Publication statusPublished - 1 Dec 2013

Keywords

  • Microarrays
  • Pain genes
  • Protein interaction network
  • Protein-protein interactions
  • Systems biology
  • Web-based resource

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