Venkatesan Aravind, Kim Jee-Hyub, Talo Francesco, Ide-Smith Michele, Gobeill Julien, Carter Jacob, Batista-Navarro Riza, Ananiadou Sophia, Ruch Patrick, McEntyre Johanna
Literature Service group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
SIB Text Mining, Swiss Institute of Bioinformatics, Geneva, Switzerland.
Wellcome Open Res. 2017 Jul 10;1:25. doi: 10.12688/wellcomeopenres.10210.2. eCollection 2016.
The tremendous growth in biological data has resulted in an increase in the number of research papers being published. This presents a great challenge for scientists in searching and assimilating facts described in those papers. Particularly, biological databases depend on curators to add highly precise and useful information that are usually extracted by reading research articles. Therefore, there is an urgent need to find ways to improve linking literature to the underlying data, thereby minimising the effort in browsing content and identifying key biological concepts. As part of the development of Europe PMC, we have developed a new platform, SciLite, which integrates text-mined annotations from different sources and overlays those outputs on research articles. The aim is to aid researchers and curators using Europe PMC in finding key concepts more easily and provide links to related resources or tools, bridging the gap between literature and biological data.
生物数据的迅猛增长导致发表的研究论文数量增加。这给科学家搜索和吸收这些论文中描述的事实带来了巨大挑战。特别是，生物数据库依赖于编目员添加通常通过阅读研究文章提取的高度精确和有用的信息。因此，迫切需要找到改进将文献与基础数据相链接的方法，从而最大限度地减少浏览内容和识别关键生物学概念的工作量。 作为欧洲PMC开发的一部分，我们开发了一个新平台SciLite，该平台整合了来自不同来源的文本挖掘注释，并将这些输出叠加在研究文章上。目的是帮助使用欧洲PMC的研究人员和编目员更轻松地找到关键概念，并提供与相关资源或工具的链接，弥合文献与生物数据之间的差距。
