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Annotation of gene product function from high-throughput studies using the Gene Ontology.

Authors :
Attrill H
Gaudet P
Huntley RP
Lovering RC
Engel SR
Poux S
Van Auken KM
Georghiou G
Chibucos MC
Berardini TZ
Wood V
Drabkin H
Fey P
Garmiri P
Harris MA
Sawford T
Reiser L
Tauber R
Toro S
Source :
Database : the journal of biological databases and curation [Database (Oxford)] 2019 Jan 01; Vol. 2019. Date of Electronic Publication: 2019 Jan 01.
Publication Year :
2019

Abstract

High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community.

Details

Language :
English
ISSN :
1758-0463
Volume :
2019
Database :
MEDLINE
Journal :
Database : the journal of biological databases and curation
Publication Type :
Academic Journal
Accession number :
30715275
Full Text :
https://doi.org/10.1093/database/baz007