SciLite: a platform for displaying text-mined annotations as a means to link research articles with biological data

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 pre...

Full description

Saved in:
Bibliographic Details
Published inWellcome open research Vol. 1; p. 25
Main Authors Venkatesan, Aravind, Kim, Jee-Hyub, Talo, Francesco, Ide-Smith, Michele, Gobeill, Julien, Carter, Jacob, Batista-Navarro, Riza, Ananiadou, Sophia, Ruch, Patrick, McEntyre, Johanna
Format Journal Article
LanguageEnglish
Published London Wellcome Trust Limited 10.07.2017
F1000Research
Wellcome
Subjects
Annotations
Automation
Bioinformatics
Biology
Collaboration
Disease
Genes
Indexing services
Life sciences
Metadata
Methods
Ontology
Proteins
Research methodology
Resource Description Framework-RDF
Semantics
Software
Software Tool
Supervision
Tagging
Writing
United Kingdom > UK
Switzerland
Online AccessGet full text

Cover

More Information
Summary: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.
Bibliography:new_version
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Equal contributors
AV contributed to the data integration aspects of SciLite and wrote the manuscript; JHK, FT designed and implemented the SciLite text-mining pipeline and front-end component; MIS worked on project management, conducted user research, front-end design of annotations on Europe PMC; JC and RBN designed and worked on NaCTeM annotation extraction; SA guided and conceived NaCTeM annotation extraction; JG designed and extracted GeneRIF dataset; PR conceived extraction of GeneRIF dataset within Elixir-EXCELERATE project. JM conceived SciLite and co-authored the manuscript. All the authors approved the final manuscript.
Competing interests: No competing interests were disclosed.
ISSN:2398-502X
2398-502X
DOI:10.12688/wellcomeopenres.10210.2