Evidence map›Paper›PMID 22123736›Full record

ArticleNucleic acids research2012

The UniProt-GO Annotation database in 2011.

Emily C Dimmer, Rachael P Huntley, Yasmin Alam-Faruque, Tony Sawford, Claire O'Donovan, Maria J Martin, Benoit Bely, Paul Browne, Wei Mun Chan, Ruth Eberhardt and 45 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 259 papers.

0numbers the graph read from it
0cells of the map it votes in
259citing 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

259 citing papers in PubMed.

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199 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

55 authors.

Emily C DimmerEuropean Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. edimmer@ebi.ac.uk
Rachael P Huntley
Yasmin Alam-Faruque
Tony Sawford
Claire O'Donovan
Maria J Martin
Benoit Bely
Paul Browne
Wei Mun Chan
Ruth Eberhardt
Michael Gardner
Kati Laiho
Duncan Legge
Michele Magrane
Klemens Pichler
Diego Poggioli
Harminder Sehra
Andrea Auchincloss
Kristian Axelsen
Marie-Claude Blatter
Emmanuel Boutet
Silvia Braconi-Quintaje
Lionel Breuza
Alan Bridge
Elizabeth Coudert
Anne Estreicher
Livia Famiglietti
Serenella Ferro-Rojas
Marc Feuermann
Arnaud Gos
Nadine Gruaz-Gumowski
Ursula Hinz
Chantal Hulo
Janet James
Silvia Jimenez
Florence Jungo
Guillaume Keller
Phillippe Lemercier
Damien Lieberherr
Patrick Masson
Madelaine Moinat
Ivo Pedruzzi
Sylvain Poux
Catherine Rivoire
Bernd Roechert
Michael Schneider
Andre Stutz
Shyamala Sundaram
Michael Tognolli
Lydie Bougueleret
Ghislaine Argoud-Puy
Isabelle Cusin
Paula Duek-Roggli
Ioannis Xenarios
Rolf Apweiler

Funding

Gene Ontology ConsortiumP41HG002273 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A · 2004 to 2011
$27.4M
UniProt: A Centralized Protein Sequence and Function ResourceU41HG006104 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI APWEILER, ROLF · 2010 to 2014
$23.5M
British Heart Foundation SP:07/007/23671NHGRI NIH HHS 1U41HG006104-02NHGRI NIH HHS 3P41HG002273-09
6 · The paper itself

Abstract

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360,000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.

Indexed as

Databases, ProteinMolecular Sequence AnnotationVocabulary, Controlled

Identifiers

PMID22123736
PMCPMC3245010

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.