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The UniProt-GO Annotation database in 2011.

Emily C Dimmer¹, Rachael P Huntley, Yasmin Alam-Faruque

¹European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. edimmer@ebi.ac.uk

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Summary

This summary is machine-generated.

The UniProt GO annotation dataset offers millions of evidenced-based protein annotations, enhancing functional information for diverse species. This resource ensures data correctness and accessibility through manual and automatic curation methods.

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Area of Science:

Bioinformatics
Proteomics
Genomics

Background:

The UniProt GO annotation dataset (GOA) links Gene Ontology (GO) terms to UniProtKB proteins.
It has grown significantly, now encompassing over 100 million annotations for 11 million proteins across 360,000 taxa.
The dataset has undergone rigorous checks for accuracy and consistency, with enhanced information content due to GO Consortium format developments.

Purpose of the Study:

To provide a comprehensive, evidenced-based dataset of protein functional annotations.
To ensure data quality through manual curation and automated predictions.
To make functional information accessible for a wide range of proteins, including those from understudied species.

Main Methods:

Manual GO annotations are derived from peer-reviewed literature by UniProt curators.
Manual and electronic annotations are contributed by 36 model organism and domain-focused resources.
High-quality, automatic annotation predictions are included to cover poorly characterized species.

Main Results:

The dataset now contains over 100 million annotations for 11 million proteins.
The resource has doubled in size over the past two years.
Functional information is supplied to a broad spectrum of proteins, including those from non-model organisms.

Conclusions:

The UniProt GO annotation dataset is a vital, expanding resource for protein functional information.
Data quality is maintained through multiple curation and validation strategies.
The dataset is freely available in various formats for broad accessibility and ease of use.