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      Reorganizing the protein space at the Universal Protein Resource (UniProt)

      research-article
      Author(s): The UniProt Consortium 1 , 2 , 3 , 4 , *
      Publication date (Electronic):
      Journal: Nucleic Acids Research
      Publisher: Oxford University Press

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          Abstract

          The mission of UniProt is to support biological research by providing a freely accessible, stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces. UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. A key development at UniProt is the provision of complete, reference and representative proteomes. UniProt is updated and distributed every 4 weeks and can be accessed online for searches or download at http://www.uniprot.org.

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          Most cited references11

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          UniRef: comprehensive and non-redundant UniProt reference clusters.

          Baris Suzek, Hongzhan Huang, Peter McGarvey … (2007)
          Redundant protein sequences in biological databases hinder sequence similarity searches and make interpretation of search results difficult. Clustering of protein sequence space based on sequence similarity helps organize all sequences into manageable datasets and reduces sampling bias and overrepresentation of sequences. The UniRef (UniProt Reference Clusters) provide clustered sets of sequences from the UniProt Knowledgebase (UniProtKB) and selected UniProt Archive records to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences. Currently covering >4 million source sequences, the UniRef100 database combines identical sequences and subfragments from any source organism into a single UniRef entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences at the 90 or 50% sequence identity levels. UniRef100, UniRef90 and UniRef50 yield a database size reduction of approximately 10, 40 and 70%, respectively, from the source sequence set. The reduced redundancy increases the speed of similarity searches and improves detection of distant relationships. UniRef entries contain summary cluster and membership information, including the sequence of a representative protein, member count and common taxonomy of the cluster, the accession numbers of all the merged entries and links to rich functional annotation in UniProtKB to facilitate biological discovery. UniRef has already been applied to broad research areas ranging from genome annotation to proteomics data analysis. UniRef is updated biweekly and is available for online search and retrieval at http://www.uniprot.org, as well as for download at ftp://ftp.uniprot.org/pub/databases/uniprot/uniref. Supplementary data are available at Bioinformatics online.
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            Ensembl 2009

            T. J. P. Hubbard, B. L. Aken, S. Ayling … (2009)
            The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases, and other information for chordate, selected model organism and disease vector genomes. As of release 51 (November 2008), Ensembl fully supports 45 species, and three additional species have preliminary support. New species in the past year include orangutan and six additional low coverage mammalian genomes. Major additions and improvements to Ensembl since our previous report include a major redesign of our website; generation of multiple genome alignments and ancestral sequences using the new Enredo-Pecan-Ortheus pipeline and development of our software infrastructure, particularly to support the Ensembl Genomes project (http://www.ensemblgenomes.org/).
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              The International Protein Index: an integrated database for proteomics experiments.

              Paul Kersey, Jorge Duarte, Allyson Williams … (2004)
              Despite the complete determination of the genome sequence of several higher eukaryotes, their proteomes remain relatively poorly defined. Information about proteins identified by different experimental and computational methods is stored in different databases, meaning that no single resource offers full coverage of known and predicted proteins. IPI (the International Protein Index) has been developed to address these issues and offers complete nonredundant data sets representing the human, mouse and rat proteomes, built from the Swiss-Prot, TrEMBL, Ensembl and RefSeq databases.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Journal ID (hwp): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date Collection: January 2012
                Publication date (Print): January 2012
                Publication date (Electronic): 17 November 2011
                Publication date PMC-release: 17 November 2011
                Volume: 40
                Issue: D1 , Database issue
                Pages: D71-D75
                Affiliations
                1The EMBL Outstation, The European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, 2SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland, 3Protein Information Resource, Georgetown University Medical Center, 3300 Whitehaven St NW, Suite 1200, Washington, DC 20007 and 4University of Delaware, 15 Innovation Way, Suite 205, Newark, DE 19711, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +44 1223 494435; Fax: +44 1223 494468; Email: apweiler@ 123456ebi.ac.uk
                Article
                Publisher ID: gkr981
                DOI: 10.1093/nar/gkr981
                PMC ID: 3245120
                PubMed ID: 22102590
                SO-VID: 9b17224a-97d3-47c4-b609-eff68ea62660
                Copyright © © The Author(s) 2011. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 29 September 2011
                Date accepted : 14 October 2011
                Page count
                Pages: 5
                Categories
                Subject: Articles

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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