Evidence map›Paper›PMID 14681408›Full record

ArticleNucleic acids research2004

The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology.

Evelyn Camon, Michele Magrane, Daniel Barrell, Vivian Lee, Emily Dimmer, John Maslen, David Binns, Nicola Harte, Rodrigo Lopez, Rolf Apweiler

Abstract read
In one paragraph

Article in Nucleic acids research, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 401 papers.

0numbers the graph read from it
0cells of the map it votes in
401citing 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

401 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
  5. Ensembl 2026.Nucleic acids research · 2026
    Article
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  9. Article
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  12. Single Cell Transcriptomic Profiling ofJournal of the American Heart Association · 2025
    Article
  13. Article
  14. Article
  15. Macrotranscriptomics analysis for decoding the role ofFrontiers in bioengineering and biotechnology · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

341 more citing papers are in PubMed but not listed here.

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.

Evelyn CamonEuropean Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. goa@ebi.ac.uk
Michele Magrane
Daniel Barrell
Vivian Lee
Emily Dimmer
John Maslen
David Binns
Nicola Harte
Rodrigo Lopez
Rolf Apweiler

Funding

GENE ONTOLOGY CONSORTIUMR01HG002273 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A · 2001 to 2003
$5.8M
NHGRI NIH HHS 1R01HGO2273-01
6 · The paper itself

Abstract

The Gene Ontology Annotation (GOA) database (http://www.ebi.ac.uk/GOA) aims to provide high-quality electronic and manual annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized vocabulary of the Gene Ontology (GO). As a supplementary archive of GO annotation, GOA promotes a high level of integration of the knowledge represented in UniProt with other databases. This is achieved by converting UniProt annotation into a recognized computational format. GOA provides annotated entries for nearly 60,000 species (GOA-SPTr) and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort. By integrating GO annotations from other model organism groups, GOA consolidates specialized knowledge and expertise to ensure the data remain a key reference for up-to-date biological information. Furthermore, the GOA database fully endorses the Human Proteomics Initiative by prioritizing the annotation of proteins likely to benefit human health and disease. In addition to a non-redundant set of annotations to the human proteome (GOA-Human) and monthly releases of its GO annotation for all species (GOA-SPTr), a series of GO mapping files and specific cross-references in other databases are also regularly distributed. GOA can be queried through a simple user-friendly web interface or downloaded in a parsable format via the EBI and GO FTP websites. The GOA data set can be used to enhance the annotation of particular model organism or gene expression data sets, although increasingly it has been used to evaluate GO predictions generated from text mining or protein interaction experiments. In 2004, the GOA team will build on its success and will continue to supplement the functional annotation of UniProt and work towards enhancing the ability of scientists to access all available biological information. Researchers wishing to query or contribute to the GOA project are encouraged to email: goa@ebi.ac.uk.

Indexed as

Databases, GeneticDatabases, ProteinGenesTerminology as TopicAnimalsComputational BiologyHumansInformation Storage and RetrievalInternetProteomeProteomicsProteome

Identifiers

PMID14681408
PMCPMC308756

What OpenQuestion holds

Textmetadata
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.