BioGPS: building your own mash-up of gene annotations and expression profiles

Abstract

BioGPS (http://biogps.org) is a centralized gene-annotation portal that enables researchers to access distributed gene annotation resources. This article focuses on the updates to BioGPS since our last paper (2013 database issue). The unique features of BioGPS, compared to those of other gene portals, are its community extensibility and user customizability. Users contribute the gene-specific resources accessible from BioGPS ('plugins'), which helps ensure that the resource collection is always up-to-date and that it will continue expanding over time (since the 2013 paper, 162 resources have been added, for a 34% increase in the number of resources available). BioGPS users can create their own collections of relevant plugins and save them as customized gene-report pages or 'layouts' (since the 2013 paper, 488 user-created layouts have been added, for a 22% increase in the number of layouts). In addition, we recently updated the most popular plugin, the 'Gene expression/activity chart', to include ∼ 6000 datasets (from ∼ 2000 datasets) and we enhanced user interactivity. We also added a new 'gene list' feature that allows users to save query results for future reference.

Figure 1.

BioGPS is built upon four key components: plugins, layouts, genes/gene lists, and datasets. Plugins are the collection of gene-specific web-resources contributed by users. Layouts are the user-customized gene report pages with selected plugins from the plugin library. Genes are the entry point for users to search for genes and link to their relevant gene-report layouts; and gene lists are users’ saved genes from their previous queries. Datasets are those BioGPS-specific reference gene expression datasets and additional ∼6000 datasets loaded from ArrayExpress. They can be visualized in one of the most popular BioGPS plugins, ‘Gene expression/activity chart’ plugin (or ‘data chart’ plugin). These components enable BioGPS users to view their own customized gene report layouts with relevant resources or datasets, depending on their own research fields, e.g. structural biology, genetics or system biology.