Abstract
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.
Highlights
The section has being reworked. - Section 2
- Sub-section 2.1 provides an overview of the architecture of SciLite - Sub-section 2.2 has been expanded to include new annotations types. - Sub-section 2.3 provides an overview of the Web Annotation model. - Sub-section 2.4 has been reworked. - Sub-section 2.5 includes a new Figure (4) that provides an overview on the feedback mechanism. - Section 3 provides details on how the user research was conducted
The section has been restructured with two new sub sections: - 3.1 – Engagement with text-mining community - 3.2 – Future directions
Summary
The section has being reworked. - Section 2. - Sub-section 2.1 provides an overview of the architecture of SciLite - Sub-section 2.2 has been expanded to include new annotations types (gene-disease relationships and manually curated protein-protein interactions). Methods: Sub-section 2.1 (Architecture) provides an overview of the architecture of SciLite (includes new figure 1) Sub-section 2.2 (Annotation types) has been expand to include new annotations types (gene-disease relationships and manually curated protein-protein interactions). Sub-section 2.5 includes a new figure (4) that provides an overview on the feedback mechanism. The section highlights the rationale behind the development of SciLite in comparison with other tools
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