Evidence map›Paper›PMID 20973947›Full record

ArticleBMC bioinformatics2010

Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development.

Jennifer I Deegan née Clark, Emily C Dimmer, Christopher J Mungall

Abstract read
In one paragraph

Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

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0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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  6. Article
  7. A roadmap for the functional annotation of protein families: a community perspective.Database : the journal of biological databases and curation · 2022
    Article
  8. Article
  9. PANTHER: Making genome-scale phylogenetics accessible to all.Protein science : a publication of the Protein Society · 2022
    Review
  10. Review
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  12. Article
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  15. Article
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  19. Article
  20. Canto: an online tool for community literature curation.Bioinformatics (Oxford, England) · 2014
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Jennifer I Deegan née ClarkEuropean Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. jdeegan@ebi.ac.uk
Emily C Dimmer
Christopher J Mungall

Funding

NHGRI NIH HHS HG002273
6 · The paper itself

Abstract

backgroundThe Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation.

resultsWe have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology.

conclusionsDetection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at https://sourceforge.net/tracker/?atid=605890&group_id=36855.

Indexed as

ClassificationDatabases, GeneticDatabases, ProteinMolecular Sequence AnnotationTerminology as TopicVocabulary, Controlled

Identifiers

PMID20973947
PMCPMC3098089

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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.