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UniRef: comprehensive and non-redundant UniProt reference clusters
Open accessAbstract
MOTIVATION: 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. RESULTS: 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. AVAILABILITY: 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 INFORMATION: Supplementary data are available at Bioinformatics online.
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“The second set contains 1964 unique mammalian protein complexes filtered against the IntAct43 dataset from Negatome31.”
From Improved prediction of protein-protein interactions using AlphaFold2 (2021) · cites this paper as [43]
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Cites
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences
Li, W.-Z., & Godzik, A. (2006) · Bioinform. · doi:10.1093/bioinformatics/btl158 · Cited by 10,996
Database resources of the National Center for Biotechnology Information: update
Wheeler, D. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh073 · Cited by 10,695
Pruitt, K. D., Tatusova, T. A., & Maglott, D. R. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl842 · Cited by 4,441
The Universal Protein Resource (UniProt)
Bairoch, A. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki070 · Cited by 3,774
The Universal Protein Resource (UniProt): an expanding universe of protein information
Wu, C. H. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj161 · Cited by 1,116
Self-citationClustering of highly homologous sequences to reduce the size of large protein databases
Li, W.-Z., Jaroszewski, L., & Godzik, A. (2001) · Bioinform. · doi:10.1093/bioinformatics/17.3.282 · Cited by 1,021
Length-dependent prediction of protein intrinsic disorder
Peng, K., Predrag Radivojac, A., Vučetić, S., Dunker, A. K., & Zoran Obradovic, A. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-208 · Cited by 940
Selection of representative protein data sets
Hobohm, U., Scharf, M. E., Schneider, R., & Sander, C. (1992) · Protein Science · doi:10.1002/pro.5560010313 · Cited by 816
Identification of multiple distinct Snf2 subfamilies with conserved structural motifs
Flaus, A. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl295 · Cited by 750
Database resources of the National Center for Biotechnology Information
Wheeler, D. L., Barrett, T., Benson, D. A., Bryant, S. H., Canese, K., Chetvernin, V., Church, D. M., DiCuccio, M., Edgar, R., Federhen, S., et al. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkl1031 · Cited by 734
Hubbard, T., Aken, B. L., Beal, K. M., Ballester, B., Cáccamo, M., Chen, Y., Clarke, L., Coates, G. M. P., Cunningham, F. M., Cutts, T., et al. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl996 · Cited by 642
The Universal Protein Resource (UniProt)
The UniProt Consortium (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl929 · Cited by 572
The RCSB PDB information portal for structural genomics
Kouranov, A. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj120 · Cited by 523
A Conserved Supergene Locus Controls Colour Pattern Diversity in Heliconius Butterflies
Joron, M., Papa, R., Beltrán, M., Chamberlain, N. L., Mavárez, J., Baxter, S. W., Abanto, M., Bermingham, E., Humphray, S., Rogers, J., et al. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040303 · Cited by 298
Genome Organization of More Than 300 Defensin-Like Genes in Arabidopsis
Silverstein, K. A. T., Graham, M. A., Paape, T. D., & VandenBosch, K. A. (2005) · PLANT PHYSIOLOGY · doi:10.1104/pp.105.060079 · Cited by 265
The Abundance of Short Proteins in the Mammalian Proteome
Frith, M. C., Forrest, A. R. R., Nourbakhsh, E., Pang, K. C., Kai, C., Kawai, J., Carninci, P., Hayashizaki, Y., Bailey, T. L., & Grimmond, S. M. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020052 · Cited by 234
Leinonen, R., Diez, F. G., Binns, D., Fleischmann, W., López, R., & Apweiler, R. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth191 · Cited by 217
Refinement and prediction of protein prenylation motifs
Maurer‐Stroh, S., & Eisenhaber, F. (2005) · Genome biology · doi:10.1186/gb-2005-6-6-r55 · Cited by 203
GeneRAGE: a robust algorithm for sequence clustering and domain detection
Enright, A. J., & Ouzounis, C. A. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.5.451 · Cited by 200
Proteomic and Bioinformatic Characterization of the Biogenesis and Function of Melanosomes
Chi, A., Valencia, J. C., Hu, Z.-Z., Watabe, H., Yamaguchi, H., Mangini, N. J., Huang, H., Canfield, V. A., Cheng, K. C., Yang, F., et al. (2006) · Journal of Proteome Research · doi:10.1021/pr060363j · Cited by 199
Self-citationAutoFACT: An Auto matic F unctional A nnotation and C lassification T ool
Koski, L. B., Gray, M. W., Lang, B. F., & Burger, G. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-151 · Cited by 189
The TIGR Plant Transcript Assemblies database
Childs, K. L., Hamilton, J. P., Zhu, W., Ly, E., Cheung, F., Wu, H., Rabinowicz, P. D., Town, C. D., Buell, C. R., & Chan, A. P.-Y. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl785 · Cited by 188
Spectral clustering of protein sequences
Paccanaro, A. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj515 · Cited by 177
Comprehensive Structural Analysis of the Genome of Red Clover (Trifolium pratense L.)
Sato, S., Isobe, S., Asamizu, E., Ohmido, N., Kataoka, R., Nakamura, Y., Kaneko, T., Sakurai, N., Okumura, K., Klimenko, I. A., et al. (2005) · DNA Research · doi:10.1093/dnares/dsi018 · Cited by 161
Sequencing and Analysis of Common Bean ESTs. Building a Foundation for Functional Genomics
Ramı́rez, M., Graham, M. A., Blanco-López, L., Silvente, S. T., Medrano-Soto, A., Blair, M. W., Hernández, G., Vance, C. P., & Lara, M. (2005) · PLANT PHYSIOLOGY · doi:10.1104/pp.104.054999 · Cited by 148
UniqueProt: creating representative protein sequence sets
Mika, S. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg620 · Cited by 121
Luscombe, N. M., Qian, J. X., Zhang, Z., Johnson, T., & Gerstein, M. (2002) · Genome biology · doi:10.1186/gb-2002-3-8-research0040 · Cited by 115
Highly syntenic regions in the genomes of soybean, Medicago truncatula, and Arabidopsis thaliana
Mudge, J., Cannon, S. B., Kaló, P., Oldroyd, G. E. D., Roe, B. A., Town, C. D., & Young, N. D. (2005) · BMC Plant Biology · doi:10.1186/1471-2229-5-15 · Cited by 109
Tetrahymena Genome Database (TGD): a new genomic resource for Tetrahymena thermophila research
Stover, N. A. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj054 · Cited by 107
Generation, annotation, analysis and database integration of 16,500 white spruce EST clusters
Pavy, N., Paule, C., Parsons, L. S., Crow, J., Morency, M., Cooke, J. E. K., Johnson, J. E., Noumen, E., Guillet-Claude, C., Butterfield, Y. S. N., et al. (2005) · BMC Genomics · doi:10.1186/1471-2164-6-144 · Cited by 107
Yan, H., Ito, H., Nobuta, K., Ouyang, S., Jin, W., Tian, S., Lu, C., Venu, R. C., Wang, G., Green, P. J., et al. (2006) · The Plant Cell · doi:10.1105/tpc.106.043794 · Cited by 104
ProClust: improved clustering of protein sequences with an extended graph-based approach
Pipenbacher, P., Schliep, A., Schneckener, S., Schönhuth, A., Schomburg, D., & Schrader, R. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_2.s182 · Cited by 89
Incorporating background frequency improves entropy-based residue conservation measures
Wang, K., & Samudrala, R. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-385 · Cited by 86
Structure of human semicarbazide-sensitive amine oxidase/vascular adhesion protein-1
Jakobsson, E., Nilsson, J., Ogg, D., & Kleywegt, G. J. (2005) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444905028805 · Cited by 85
Pavy, N., Parsons, L. S., Paule, C., MacKay, J. J., & Bousquet, J. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-174 · Cited by 76
Databases and Information Integration for the Medicago truncatula Genome and Transcriptome
Cannon, S. B., Crow, J., Heuer, M., Wang, X., Cannon, E. K. S., Dwan, C., Lamblin, A.-F., Vasdewani, J., Mudge, J., Cook, A., et al. (2005) · PLANT PHYSIOLOGY · doi:10.1104/pp.104.059204 · Cited by 63
A normalised scale for structural genomics target ranking: The OB‐Score
Overton, I. M., & Barton, G. J. (2006) · FEBS Letters · doi:10.1016/j.febslet.2006.06.015 · Cited by 57
Comparative bioinformatics analyses and profiling of lysosome-related organelle proteomes
Hu, Z.-Z., Valencia, J. C., Huang, H., Chi, A., Shabanowitz, J., Hearing, V. J., Appella, E., & Wu, C. H. (2006) · International Journal of Mass Spectrometry · doi:10.1016/j.ijms.2006.09.024 · Cited by 51
Self-citationThe predictive power of the CluSTr database
Petryszak, R., Kretschmann, E., Wieser, D., & Apweiler, R. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti542 · Cited by 50
Ng, A. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj044 · Cited by 45
Saturating representation of loop conformational fragments in structure databanks.
Fernández‐Fuentes, N., & Fiser, A. (2006) · BMC Structural Biology · doi:10.1186/1472-6807-6-15 · Cited by 43
Proteome profiling of human epithelial ovarian cancer cell line TOV-112D
Gagné, J., Gagné, P., Hunter, J. M., Bonicalzi, M.-È., Lemay, J., Kelly, I., Page, C. L., Provencher, D. M., Mes‐Masson, A., Droit, A., et al. (2005) · Molecular and Cellular Biochemistry · doi:10.1007/s11010-005-7556-1 · Cited by 42
Kinjo, A. R., & Nishikawa, K. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-401 · Cited by 41
RSDB: representative protein sequence databases have high information content
Bhak, J., Holm, L., Heger, A., & Chothia, C. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.5.458 · Cited by 40
Death inducer obliterator protein 1 in the context of DNA regulation
Rojas, A. M., Sánchez‐Pulido, L., Fütterer, A., van Wely, K. H. M., Martínez‐A, C., & Valencia, A. (2005) · FEBS Journal · doi:10.1111/j.1742-4658.2005.04759.x · Cited by 40
Conklin, D., Jonassen, I., Aasland, R., & Taylor, W. R. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.1.182 · Cited by 31
Challenges and Solutions in Proteomics
Huang, H., Shukla, H. D., Wu, C. H., & Saxena, S. P. (2007) · Current Genomics · doi:10.2174/138920207780076910 · Cited by 26
Self-citationHigh throughput profile-profile based fold recognition for the entire human proteome
McGuffin, L. J., Smith, R. T., Bryson, K., Sørensen, S.-A., & Jones, D. T. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-288 · Cited by 23
On single and multiple models of protein families for the detection of remote sequence relationships
Casbon, J. A., & Saqi, M. A. S. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-48 · Cited by 12
Vgenopoulou, I., Gemperli, A. C., & Steuber, J. (2006) · Journal of Bacteriology · doi:10.1128/jb.188.9.3264-3272.2006 · Cited by 10
DOUTfinder--identification of distant domain outliers using subsignificant sequence similarity
Novatchkova, M., Schneider, G., Fritz, R., Eisenhaber, F., & Schleiffer, A. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl332 · Cited by 9
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Metadata
- Authors
- Suzek, B. E., Huang, H., McGarvey, P., Mazumder, R., & Wu, C. H.
- Affiliations
- Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA
- Georgetown University Medical Center (US)
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-03-22
- Volume
- 23
- Issue
- 10
- Pages
- 1282-1288
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2076048958
- Cited by
- 1,613
- References
- 51
- Citations by year
- 2026: 137 · 2025: 197 · 2024: 164 · 2023: 132 · 2022: 93 · 2021: 84 · 2020: 68 · 2019: 69 · 2018: 55 · 2017: 74 · 2016: 87 · 2015: 91 · 2014: 64 · 2013: 82 · 2012: 63
- FWCI
- 13.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- European Bioinformatics Institute
- National Institutes of Health
- National Human Genome Research Institute (U01HG02712, U01HG002712)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- protein sequence clustering, sequence similarity search, protein sequence space, distant homology detection, functional annotation
- MeSH terms
- Amino Acid Sequence, Animals, Humans, Proteins, Information Storage and Retrieval, Computational Biology, Databases, Protein
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