Evidence map›Paper›PMID 27812933›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2017

Primer on the Gene Ontology.

Pascale Gaudet, Nives Škunca, James C Hu, Christophe Dessimoz

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing 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

58 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Identification of potential biomarkers for hypertension based on transcriptomic analysis in rats.Hypertension research : official journal of the Japanese Society of Hypertension · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. A cell atlas of thoracic aortic perivascular adipose tissue: a focus on mechanotransducers.American journal of physiology. Heart and circulatory physiology · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Adjustment ofFrontiers in genetics · 2023
    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

4 authors.

Pascale GaudetCALIPHO group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 Michel-Servet, 1211, Geneva, Switzerland. pascale.gaudet@sib.swiss.
Nives ŠkuncaDepartment of Computer Science, ETH Zurich, Universitätstrasse 19, 8092, Zurich, Switzerland.
James C HuDepartment of Biochemistry and Biophysics, Texas A&M University and Texas AgriLife Research, College Station, TX, USA.
Christophe DessimozDepartment of Genetics, Evolution & Environment, University College London, Gower St, London, WC1E 6BT, UK.

Funding

Resource ProjectU41HG002273 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHERRY, J. MICHAEL, MUNGALL, CHRISTOPHER J · 2012 to 2021
$34.7M
Gene Ontology ConsortiumP41HG002273 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A · 2004 to 2011
$27.4M
GENE ONTOLOGY CONSORTIUMR01HG002273 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A · 2001 to 2003
$5.8M
EcoliHub2.0: A next-generation E. coli model organism resource (SRI Proposal ECU U24GM088849 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI HU, JAMES C, SHERLOCK, GAVIN J · 2009 to 2012
$4.4M
An Ontology for Microbial PhenotypesR01GM089636 · NIGMS · TEXAS A&M UNIVERSITY · PI HU, JAMES C · 2010 to 2016
$1.6M
Biotechnology and Biological Sciences Research CouncilNHGRI NIH HHS P41 HG002273NHGRI NIH HHS R01 HG002273NHGRI NIH HHS U41 HG002273NIGMS NIH HHS R01 GM089636NIGMS NIH HHS U24 GM088849
6 · The paper itself

Abstract

The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essential resource for data analysis. In this chapter, we provide a concise primer for all users of the GO. We briefly introduce the structure of the ontology and explain how to interpret annotations associated with the GO.

Indexed as

Gene OntologyAnimalsComputational BiologyDatabases, GeneticDNAHumansInternetProteinsRNADNAProteinsRNAAnnotation evidenceAnnotationsEvidence codesFunctionGene association file (GAF)Gene Ontology structureGO filesVocabulary

Identifiers

PMID27812933
PMCPMC6377150

What OpenQuestion holds

Textmetadata
LicenceTDM
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.