Evidence map›Paper›PMID 26825309›Full record

ArticleNeuroinformatics2016

Using the Gene Ontology to Annotate Key Players in Parkinson's Disease.

R E Foulger, P Denny, J Hardy, M J Martin, T Sawford, R C Lovering

Abstract read
In one paragraph

Article in Neuroinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. A review on Gene Ontology evaluations.Database : the journal of biological databases and curation · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. 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

6 authors.

R E FoulgerCentre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK. rebecca.foulger@ucl.ac.uk.
P DennyCentre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK.
J HardyDepartment of Molecular Neuroscience, Institute of Neurology, University College London, London, UK.
M J MartinEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK.
T SawfordEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK.
R C LoveringCentre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK.

Funding

Resource ProjectU41HG002273 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHERRY, J. MICHAEL, MUNGALL, CHRISTOPHER J · 2012 to 2021
$34.7M
British Heart Foundation RG/13/5/30112Medical Research CouncilNHGRI NIH HHS U41 HG002273Parkinson's UK G-1307Wellcome TrustWellcome Trust WT089698
6 · The paper itself

Abstract

The Gene Ontology (GO) is widely recognised as the gold standard bioinformatics resource for summarizing functional knowledge of gene products in a consistent and computable, information-rich language. GO describes cellular and organismal processes across all species, yet until now there has been a considerable gene annotation deficit within the neurological and immunological domains, both of which are relevant to Parkinson's disease. Here we introduce the Parkinson's disease GO Annotation Project, funded by Parkinson's UK and supported by the GO Consortium, which is addressing this deficit by providing GO annotation to Parkinson's-relevant human gene products, principally through expert literature curation. We discuss the steps taken to prioritise proteins, publications and cellular processes for annotation, examples of how GO annotations capture Parkinson's-relevant information, and the advantages that a topic-focused annotation approach offers to users. Building on the existing GO resource, this project collates a vast amount of Parkinson's-relevant literature into a set of high-quality annotations to be utilized by the research community.

Indexed as

Gene OntologyMolecular Sequence AnnotationComputational BiologyDatabases, GeneticHumansParkinson DiseaseAnnotation, databaseFunctional annotationGene ontologyHigh-throughput analysisParkinson’s disease

Identifiers

PMID26825309
PMCPMC4896971

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.