Evidence map›Paper›PMID 28948232›Full record

ArticleWellcome open research2016

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

Aravind Venkatesan, Jee-Hyub Kim, Francesco Talo, Michele Ide-Smith, Julien Gobeill, Jacob Carter, Riza Batista-Navarro, Sophia Ananiadou, Patrick Ruch, Johanna McEntyre

Abstract read
In one paragraph

Article in Wellcome open research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Europe PMC in 2023.Nucleic acids research · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Europe PMC in 2020.Nucleic acids research · 2021
    Article
  11. Article
  12. Article
  13. Article
  14. Automatic annotation of protein residues in published papers.Acta crystallographica. Section F, Structural biology communications · 2019
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Europe PMC in 2017.Nucleic acids research · 2018
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Aravind Venkatesan *Literature Service group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Jee-Hyub Kim *Literature Service group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Francesco TaloLiterature Service group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Michele Ide-SmithLiterature Service group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Julien GobeillSIB Text Mining, Swiss Institute of Bioinformatics, Geneva, Switzerland.
Jacob CarterNational Centre for Text Mining (NaCTeM), Manchester Institute of Biotechnology, Manchester, UK.
Riza Batista-NavarroNational Centre for Text Mining (NaCTeM), Manchester Institute of Biotechnology, Manchester, UK.
Sophia AnaniadouNational Centre for Text Mining (NaCTeM), Manchester Institute of Biotechnology, Manchester, UK.
Patrick RuchSIB Text Mining, Swiss Institute of Bioinformatics, Geneva, Switzerland.
Johanna McEntyreLiterature Service group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.

Funding

Wellcome Trust
6 · The paper itself

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.

Indexed as

BiocurationData IntegrationOpen AccessRDFSciLiteSemantic WebSPARQLText-MiningWeb Annotations

Identifiers

PMID28948232
PMCPMC5527546

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.