The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Reorganizing the protein space at the Universal Protein Resource (UniProt)
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
UniRef: comprehensive and non-redundant UniProt reference clusters
Suzek, B. E., Huang, H., McGarvey, P., Mazumder, R., & Wu, C. H. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm098 · Cited by 1,613
Cited by
Pfam: the protein families database
Finn, R. D., Bateman, A., Clements, J., Coggill, P., Eberhardt, R. Y., Eddy, S. R., Heger, A., Hetherington, K., Holm, L., Mistry, J., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1223 · Cited by 6,148
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585
Yang, W., Soares, J., Greninger, P., Edelman, E. J., Lightfoot, H., Forbes, S., Bindal, N., Beare, D., Smith, J. A., Thompson, I. R., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1111 · Cited by 4,051
Predicting Functional Effect of Human Missense Mutations Using PolyPhen‐2
Adzhubei, I., Jordan, D. M., & Sunyaev, S. R. (2013) · Current Protocols in Human Genetics · doi:10.1002/0471142905.hg0720s76 · Cited by 3,705
ALKBH5 Is a Mammalian RNA Demethylase that Impacts RNA Metabolism and Mouse Fertility
Zheng, G., Dahl, J. A., Niu, Y., Fedorcsak, P., Huang, C.-M., Li, C. J., Vågbø, C. B., Shi, Y., Wang, W.-L., Song, S.-H., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2012.10.015 · Cited by 3,550
A landscape of driver mutations in melanoma
Hodis, E., Watson, I. R., Kryukov, G. V., Arold, S. T., Imielinski, M., Theurillat, J.-P., Nickerson, E., Auclair, D., Li, L., Place, C., et al. (2012) · Cell · doi:10.1016/j.cell.2012.06.024 · Cited by 2,610
The Proteomics Identifications (PRIDE) database and associated tools: status in 2013
Vizcaíno, J. A., Côté, R. G., Csordas, A., Dianes, J. A., Fabregat, A., Foster, J. M., Griss, J., Alpi, E., Birim, M., Contell, J., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1262 · Cited by 1,918
The Reactome pathway knowledgebase
Croft, D., Mundo, A. F., Haw, R., Milacic, M., Weiser, J., Wu, G., Caudy, M., Garapati, P., Gillespie, M., Kamdar, M. R., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1102 · Cited by 1,889
Proteoform: a single term describing protein complexity
The Consortium for Top Down Proteomics, Smith, L. M., & Kelleher, N. L. (2013) · Nature Methods · doi:10.1038/nmeth.2369 · Cited by 1,528
The evolution of lncRNA repertoires and expression patterns in tetrapods
Necsulea, A., Soumillon, M., Warnefors, M., Liechti, A., Daish, T., Zeller, U., Baker, J. C., Grützner, F., & Kaessmann, H. (2014) · Nature · doi:10.1038/nature12943 · Cited by 984
Protein structure prediction from sequence variation
Marks, D. S., Hopf, T. A., & Sander, C. (2012) · Nature Biotechnology · doi:10.1038/nbt.2419 · Cited by 622
Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models
Ekeberg, M., Lövkvist, C., Lan, Y., Weigt, M., & Aurell, E. (2013) · Physical Review E · doi:10.1103/physreve.87.012707 · Cited by 661
Interactome3D: adding structural details to protein networks
Mosca, R., Céol, A., & Aloy, P. (2013) · Nature Methods · doi:10.1038/nmeth.2289 · Cited by 479
The WAVE regulatory complex links diverse receptors to the actin cytoskeleton
Chen, B., Brinkmann, K., Chen, Z., Pak, C. W., Liao, Y., Shi, S., Henry, L., Grishin, N. V., Bogdan, S., & Rosen, M. K. (2014) · Cell · doi:10.1016/j.cell.2013.11.048 · Cited by 323
Transcriptome analysis of human tissues and cell lines reveals one dominant transcript per gene
Gonzàlez-Porta, M., Frankish, A., Rung, J., Harrow, J., & Brazma, A. (2013) · Genome Biology · doi:10.1186/gb-2013-14-7-r70 · Cited by 266
Rask-Andersen, M., Masuram, S., & Schiöth, H. B. (2014) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-011613-135943 · Cited by 282
APPRIS: annotation of principal and alternative splice isoforms
Rodriguez, J. M., Maietta, P., Ezkurdia, I., Pietrelli, A., Wesselink, J.-J., Lopez, G., Valencia, A., & Tress, M. L. (2013) · Nucleic Acids Research · doi:10.1093/nar/gks1058 · Cited by 232
Widespread aggregation and neurodegenerative diseases are associated with supersaturated proteins
Ciryam, P., Tartaglia, G. G., Morimoto, R. I., Dobson, C. M., & Vendruscolo, M. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.09.043 · Cited by 270
Pinto, R. M., Dragileva, E., Kirby, A., Lloret, A., Lopez, E., St. Claire, J., Panigrahi, G. B., Hou, C., Holloway, K., Gillis, T., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003930 · Cited by 250
“Note that none of these variants has been identified in human MLH1 [47].”
BackgroundMany human accelerated regions are developmental enhancers
Capra, J. A., Erwin, G. D., McKinsey, G., Rubenstein, J. L. R., & Pollard, K. S. (2013) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2013.0025 · Cited by 235
An AT-hook domain in MeCP2 determines the clinical course of Rett syndrome and related disorders
Baker, S. A., Chen, L., Wilkins, A. D., Yu, P., Lichtarge, O., & Zoghbi, H. Y. (2013) · Cell · doi:10.1016/j.cell.2013.01.038 · Cited by 225
Schork, A. J., Won, H., Appadurai, V., Nudel, R., Gandal, M., Delaneau, O., Revsbech Christiansen, M., Hougaard, D. M., Bækved-Hansen, M., Bybjerg-Grauholm, J., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0320-0 · Cited by 223
Standardized benchmarking in the quest for orthologs
Quest for Orthologs consortium, Altenhoff, A. M., Boeckmann, B., Capella-Gutierrez, S., Dalquen, D. A., DeLuca, T., Forslund, K., Huerta-Cepas, J., Linard, B., Pereira, C., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3830 · Cited by 214
A Review of bioinformatics tools for bio-prospecting from metagenomic sequence data
Roumpeka, D. D., Wallace, R. J., Escalettes, F., Fotheringham, I., & Watson, M. (2017) · Frontiers in Genetics · doi:10.3389/fgene.2017.00023 · Cited by 199
“In Reactome also references other databases such as UniProt, Ensembl, KEGG and many others (Consortium, 2012; Flicek et al., 2012; Kanehisa et al., 2012; Brown et al., 2015).”
BackgroundMenschaert, G., Van Criekinge, W., Notelaers, T., Koch, A., Crappé, J., Gevaert, K., & Van Damme, P. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.027540 · Cited by 173
Compact genome of the Antarctic midge is likely an adaptation to an extreme environment
Kelley, J. L., Peyton, J. T., Fiston-Lavier, A.-S., Teets, N. M., Yee, M.-C., Johnston, J. S., Bustamante, C. D., Lee, R. E., & Denlinger, D. L. (2014) · Nature Communications · doi:10.1038/ncomms5611 · Cited by 171
ECMDB: the E-coli Metabolome Database
Guo, A. C., Jewison, T., Wilson, M., Liu, Y., Knox, C., Djoumbou, Y., Lo, P., Mandal, R., Krishnamurthy, R., & Wishart, D. S. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks992 · Cited by 164
Breast-fed and bottle-fed infant rhesus macaques develop distinct gut microbiotas and immune systems
Ardeshir, A., Narayan, N. R., Méndez-Lagares, G., Lu, D., Rauch, M., Huang, Y., Van Rompay, K. K. A., Lynch, S. V., & Hartigan-O’Connor, D. J. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3008791 · Cited by 134
Mutations in Disordered Regions Can Cause Disease by Creating Dileucine Motifs
Meyer, K., Kirchner, M., Uyar, B., Cheng, J.-Y., Russo, G., Hernandez-Miranda, L. R., Szymborska, A., Zauber, H., Rudolph, I.-M., Willnow, T. E., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.019 · Cited by 132
Li, S., Smith, K. D., Davis, J. H., Gordon, P. B., Breaker, R. R., & Strobel, S. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1310439110 · Cited by 122
Identification of Antioxidants from Sequence Information Using Naïve Bayes
Feng, P.-M., Lin, H., & Chen, W. (2013) · Computational and Mathematical Methods in Medicine · doi:10.1155/2013/567529 · Cited by 109
Rubino, F., Carberry, C., Waters, S. M., Kenny, D., McCabe, M. S., & Creevey, C. J. (2017) · The ISME Journal · doi:10.1038/ismej.2016.172 · Cited by 101
Calçada, D., Vianello, D., Giampieri, E., Sala, C., Castellani, G., de Graaf, A., Kremer, B., van Ommen, B., Feskens, E., Santoro, A., et al. (2014) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2014.01.004 · Cited by 97
Nitrogen-use efficiency in maize (Zea mays L.): from ‘omics’ studies to metabolic modelling
Simons, M., Saha, R., Guillard, L., Clement, G., Armengaud, P., Canas, R., Maranas, C. D., Lea, P. J., & Hirel, B. (2014) · Journal of Experimental Botany · doi:10.1093/jxb/eru227 · Cited by 87
Proteome-wide analysis of HIV-specific naive and memory CD4+ T cells in unexposed blood donors
Campion, S. L., Brodie, T. M., Fischer, W., Korber, B. T., Rossetti, A., Goonetilleke, N., McMichael, A. J., & Sallusto, F. (2014) · Journal of Experimental Medicine · doi:10.1084/jem.20130555 · Cited by 84
Identification of genetic variants influencing the human plasma proteome
Johansson, Å., Enroth, S., Palmblad, M., Deelder, A. M., Bergquist, J., & Gyllensten, U. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217238110 · Cited by 82
The TIM Barrel Architecture Facilitated the Early Evolution of Protein-Mediated Metabolism
Goldman, A. D., Beatty, J. T., & Landweber, L. F. (2016) · Journal of Molecular Evolution · doi:10.1007/s00239-015-9722-8 · Cited by 81
Xu, F., Jerlström-Hultqvist, J., Einarsson, E., Ástvaldsson, Á., Svärd, S. G., & Andersson, J. O. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004053 · Cited by 74
Prediction of antimicrobial peptides based on the adaptive neuro‐fuzzy inference system application
Fernandes, F. C., Rigden, D. J., & Franco, O. L. (2012) · Peptide Science · doi:10.1002/bip.22066 · Cited by 67
GPI Transamidase and GPI anchored proteins: Oncogenes and biomarkers for cancer
Gamage, D. G., & Hendrickson, T. L. (2013) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.3109/10409238.2013.831024 · Cited by 63
LUCApedia: a database for the study of ancient life
Goldman, A. D., Bernhard, T. M., Dolzhenko, E., & Landweber, L. F. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1217 · Cited by 58
Novel childhood asthma genes interact with in utero and early-life tobacco smoke exposure
Scholtens, S., Postma, D. S., Moffatt, M. F., Panasevich, S., Granell, R., Henderson, A. J., Melén, E., Nyberg, F., Pershagen, G., Jarvis, D., et al. (2014) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2013.08.049 · Cited by 51
Bell, C., English, L., Boulais, J., Chemali, M., Caron-Lizotte, O., Desjardins, M., & Thibault, P. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m112.025775 · Cited by 46
The first chromosome‐level genome for a marine mammal as a resource to study ecology and evolution
Fan, G., Zhang, Y., Liu, X., Wang, J., Sun, Z., Sun, S., Zhang, H., Chen, J., Lv, M., Han, K., et al. (2019) · Molecular Ecology Resources · doi:10.1111/1755-0998.13003 · Cited by 45
SHIRAISHI, H., & TABUSE, Y. (2013) · Bioscience, Biotechnology, and Biochemistry · doi:10.1271/bbb.120919 · Cited by 13
Gao, Y., Shen, L., & Honzatko, R. B. (2014) · Journal of Biological Chemistry · doi:10.1074/jbc.m114.548586 · Cited by 11
Extracting reaction networks from databases—opening Pandora’s box
Fearnley, L. G., Davis, M. J., Ragan, M. A., & Nielsen, L. K. (2014) · Briefings in Bioinformatics · doi:10.1093/bib/bbt058 · Cited by 9
Metadata
- Authors
- The UniProt Consortium
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-11-18
- Volume
- 40
- Issue
- D1
- Pages
- D71-D75
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W4233334497
- Cited by
- 1,220
- References
- 1
- FWCI
- 93.81
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.