Evidence map›Paper›PMID 25937883›Full record

ArticleJournal of biomedical semantics2014

TermGenie - a web-application for pattern-based ontology class generation.

Heiko Dietze, Tanya Z Berardini, Rebecca E Foulger, David P Hill, Jane Lomax, David Osumi-Sutherland, Paola Roncaglia, Christopher J Mungall

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  4. Review
  5. Article
  6. Review
  7. Dead simple OWL design patterns.Journal of biomedical semantics · 2017
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. The cellular microscopy phenotype ontology.Journal of biomedical semantics · 2016
    Article
  16. Article
  17. Article
  18. Article
  19. Gene Ontology Consortium: going forward.Nucleic acids research · 2015
    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

8 authors.

Heiko DietzeGenomics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 USA.
Tanya Z BerardiniThe Arabidopsis Information Resource, Phoenix Bioinformatics, Redwood City, CA 94063 USA.
Rebecca E FoulgerEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD UK.
David P HillMouse Genome Informatics, The Jackson Laboratory, Bar Harbor, ME 04609 USA.
Jane LomaxEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD UK.
David Osumi-SutherlandEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD UK.
Paola RoncagliaThe Arabidopsis Information Resource, Phoenix Bioinformatics, Redwood City, CA 94063 USA.
Christopher J MungallGenomics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 USA.

Funding

Resource ProjectU41HG002273 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMAS, PAUL D. · 2012 to 2021
$34.7M
Gene Ontology ConsortiumP41HG002273 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A · 2004 to 2011
$27.4M
The Monarch Initiative: Linking Diseases to Model Organism ResourcesR24OD011883 · OD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HAENDEL, MELISSA A, MUNGALL, CHRISTOPHER J · 2012 to 2024
$16.0M
NHGRI NIH HHS P41 HG002273NHGRI NIH HHS U41 HG002273NIH HHS R24 OD011883
6 · The paper itself

Abstract

backgroundBiological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes.

resultsTermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes.

conclusionTermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

Indexed as

Class generationOntology

Identifiers

PMID25937883
PMCPMC4417543

What Socratic 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 Socratic graph.