We now know of hundreds of genes that have some association with pain. Several genes have been shown to alter pain sensitivity in humans, and can be found in the OMIM database. The Pain Gene Database gives details of genes that have been shown to alter pain-related behaviour in transgenic mouse models (usually gene knockout). Genes identified in this way are often studied in isolation, or alongside a handful of other genes. Techniques from systems biology, and methods for identifying protein interactions and gene associations using data derived from functional genomics studies allow us to study these genes in the context of the biological systems and pathways on which they operate. Predicted gene associations, generated by various
bioinformatics tools, can be used to extend these associations and enrich the information available on protein networks.
Here we describe a resource, available at www.painnetworks.org,that allows the user to visualise pain genes in the context of an interaction network.
The user can also enrich the networks using data from a number of pain-focused gene expression studies to highlight genes that change in expression in a given experiment and genes showing correlated patterns of expression in a number of different experiments. The website currently contains several pain-related datasets and the user is able to input their own experiment to view alongside these datasets (without the need to send any of their data over the web). We also invite users to submit their own data to the website. We expect this resource to grow over time and become a valuable asset to the pain community.
