The Universal Protein Resource (UniProt)

By Amos Bairoch, Rolf Apweiler, Cathy H. Wu, W. C. Barker, Brigitte Boeckmann, Serenella Ferro, Elisabeth Gasteiger, Hongzhan Huang, Rodrigo Lopez, Michele Magrane and 5 more. 2004

4,459 citations recorded by the source corpus.

The Universal Protein Resource (UniProt) provides the scientific community with a single, centralized, authoritative resource for protein sequences and functional information. Formed by uniting the Swiss-Prot, TrEMBL and PIR protein database activities, the UniProt consortium produces three layers of protein sequence databases: the UniProt Archive (UniParc), the UniProt Knowledgebase (UniProt) and the UniProt Reference (UniRef) databases. The UniProt Knowledgebase is a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase with extensive cross-references. This centrepiece consists of two sections: UniProt/Swiss-Prot, with fully, manually curated entries; and UniProt/TrEMBL, enriched with automated classification and annotation. During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; we introduced a new comment line topic: TOXIC DOSE to store information on the acute toxicity of a toxin; the UniProt keyword list got augmented by additional keywords; we improved the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications. Furthermore, we introduced a new documentation file of the strains and their synonyms. Many new database cross-references were introduced and we started to make use of Digital Object Identifiers. We also achieved in collaboration with the Macromolecular Structure Database group at EBI an improved integration with structural databases by residue level mapping of sequences from the Protein Data Bank entries onto corresponding UniProt entries. For convenient sequence searches we provide the UniRef non-redundant sequence databases. The comprehensive UniParc database stores the complete body of publicly available protein sequence data. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every two weeks.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy, Computational Biology & Bioinformatics

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Citations in the corpus

Toward the estimation of the absolute quality of individual protein structure models (2010, background): “Most current scoring functions are primarily designed to rank alternative models of the same sequence supporting model selection, whereas the prediction of the absolute quality of an individual protein model has received little attention in the field.”
ProGen: Language Modeling for Protein Generation (2020, methodology): “, 2004), UniprotKB (Bairoch et al., 2005), SWISS-PROT (Bairoch et al.”
Clustering huge protein sequence sets in linear time (2017, methodology): “, 100}, we determined these thresholds empirically on 4 million local alignments sampled from an all-against-all comparison of the UniProt database [31].”
RaptorX-Property: a web server for protein structure property prediction (2016, methodology): “Since the experimental structure determination methods are laborious and expensive, as of January 2016 there are only ∼ 110 000 protein structures in PDB (5), and merely ∼ 37K of them are annotated in UniProt entries (6).”
SISYPHUS—structural alignments for proteins with non-trivial relationships (2006, background): “For each protein we provide a link to the UniProt sequence (19) and hence access to the natural protein sequence, which can be easily added to the structural alignment.”
Using MCL to extract clusters from networks. (2012, methodology): “3 Sample files Case study 1 uses fasta files downloaded from Uniprot [24] for twenty eight genomes of the order Rickettsiales, containing sequences for a total of 31374 proteins.”
The Protein Model Portal (2008, methodology): “A common reference system for target proteins is established based on the UniProt database [17] by calculating cryptographic md5 hashes for all full length amino acid sequences.”
MaGe: a microbial genome annotation system supported by synteny results (2006, methodology): “Extracted gene products are subjected to exhaustive bioinformatics analysis, including the gapped blastP algorithm (26) for general-purpose homology searches against the full nonredundant protein sequence databank UniProt (27).”