Integrating GPCR-specific information with full text articles
1 CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Geert Grooteplein 26-28, Nijmegen, 6525 GA, The Netherlands
2 School of Computer Science, University of Manchester, Kilburn Building, Oxford Road, Manchester, M13 9PL, UK
3 Faculty of Life Sciences, University of Manchester, Michael Smith Building, Oxford Road, Manchester, M13 9PT, UK
BMC Bioinformatics 2011, 12:362 doi:10.1186/1471-2105-12-362Published: 12 September 2011
With the continued growth in the volume both of experimental G protein-coupled receptor (GPCR) data and of the related peer-reviewed literature, the ability of GPCR researchers to keep up-to-date is becoming increasingly curtailed.
We present work that integrates the biological data and annotations in the GPCR information system (GPCRDB) with next-generation methods for intelligently exploring, visualising and interacting with the scientific articles used to disseminate them. This solution automatically retrieves relevant information from GPCRDB and displays it both within and as an adjunct to an article.
This approach allows researchers to extract more knowledge more swiftly from literature. Importantly, it allows reinterpretation of data in articles published before GPCR structure data became widely available, thereby rescuing these valuable data from long-dormant sources.