CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Geert Grooteplein 26-28, Nijmegen, 6525 GA, The Netherlands.
BMC Bioinformatics. 2011 Sep 12;12:362. doi: 10.1186/1471-2105-12-362.
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.
随着实验性 G 蛋白偶联受体 (GPCR) 数据量以及相关同行评审文献的持续增长,GPCR 研究人员及时了解最新信息的能力正变得越来越有限。
我们提出了一项工作,该工作将 GPCR 信息系统 (GPCRDB) 中的生物数据和注释与用于智能探索、可视化和交互使用这些数据的下一代方法相结合。该解决方案可自动从 GPCRDB 中检索相关信息,并在文章内部和作为文章的补充显示这些信息。
这种方法可以让研究人员更快地从文献中提取更多的知识。重要的是,它允许对在 GPCR 结构数据广泛可用之前发表的文章中的数据进行重新解释,从而从长期休眠的来源中抢救这些有价值的数据。