UniProt: the universal protein knowledgebase

2016 Nucleic Acids Research 4,500 citations

Abstract

The UniProt knowledgebase is a large resource of protein sequences and associated detailed annotation. The database contains over 60 million sequences, of which over half a million sequences have been curated by experts who critically review experimental and predicted data for each protein. The remainder are automatically annotated based on rule systems that rely on the expert curated knowledge. Since our last update in 2014, we have more than doubled the number of reference proteomes to 5631, giving a greater coverage of taxonomic diversity. We implemented a pipeline to remove redundant highly similar proteomes that were causing excessive redundancy in UniProt. The initial run of this pipeline reduced the number of sequences in UniProt by 47 million. For our users interested in the accessory proteomes, we have made available sets of pan proteome sequences that cover the diversity of sequences for each species that is found in its strains and sub-strains. To help interpretation of genomic variants, we provide tracks of detailed protein information for the major genome browsers. We provide a SPARQL endpoint that allows complex queries of the more than 22 billion triples of data in UniProt (http://sparql.uniprot.org/). UniProt resources can be accessed via the website at http://www.uniprot.org/.

Keywords

UniProtProteomeBiologySPARQLAnnotationPipeline (software)Human proteome projectComputational biologyComputer scienceInformation retrievalBioinformaticsProteomicsGeneticsRDFSemantic WebGene

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Publication Info

Year
2016
Type
article
Volume
45
Issue
D1
Pages
D158-D169
Citations
4500
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

4500
OpenAlex
98
Influential
4075
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Cite This

(2016). UniProt: the universal protein knowledgebase. Nucleic Acids Research , 45 (D1) , D158-D169. https://doi.org/10.1093/nar/gkw1099

Identifiers

DOI
10.1093/nar/gkw1099
PMID
29425356
PMCID
PMC5861450

Data Quality

Data completeness: 72%