QuickGO: a web-based tool for gene ontology searching
Open accessAbstract
UNLABELLED: QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups QuickGO has been a popular GO browser for many years, but after a recent redevelopment it is now able to offer a greater range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. AVAILABILITY AND IMPLEMENTATION: QuickGO has implemented in JavaScript, Ajax and HTML, with all major browsers supported. It can be queried online at http://www.ebi.ac.uk/QuickGO. The software for QuickGO is freely available under the Apache 2 licence and can be downloaded from http://www.ebi.ac.uk/QuickGO/installation.html
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Biological ontologies are large hierarchies with a DAG structure, so existing tools for visualizing ontologies can have direct application to data-driven multiscale models.
“Biological ontologies are large hierarchies which also have a DAG structure; as such, existing tools for visualizing ontologies can also have direct application to data-driven multiscale models (Binns et al., 2009; Eden et al., 2009; Sealfon et al., 2006; Supek et al., 2011; Zhu et al., 2019).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Binns et al., 2009
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The Universal Protein Resource (UniProt)
Bairoch, A. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki070 · Cited by 3,774 · see citing works
The GOA database in 2009--an integrated Gene Ontology Annotation resource
Barrell, D. G., Dimmer, E. C., Huntley, R. P., Binns, D., O’Donovan, C., & Apweiler, R. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn803 · Cited by 554 · see citing works
Self-citationThe Universal Protein Resource (UniProt) 2009
The UniProt Consortium (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn664 · Cited by 546 · see citing works
The Gene Ontology — Providing a Functional Role in Proteomic Studies
Dimmer, E. C., Huntley, R. P., Barrell, D. G., et al. (2008) · PROTEOMICS · doi:10.1002/pmic.200800002 · Cited by 50 · see citing works
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Hagai, T., Chen, X., Miragaia, R. J., Rostom, R., Gomes, T., Kunowska, N., Henriksson, J., Park, J.-E., Proserpio, V., Donati, G., et al. (2018) · Nature · doi:10.1038/s41586-018-0657-2 · Cited by 220 · see citing works
Rizvi, A. H., Camara, P. G., Kandror, E. K., Roberts, T. J., Schieren, I., Maniatis, T., & Rabadan, R. (2017) · Nature Biotechnology · doi:10.1038/nbt.3854 · Cited by 248 · see citing works
Bargehr, J., Ong, L. P., Colzani, M., Davaapil, H., Hofsteen, P., Bhandari, S., Gambardella, L., Le Novère, N., Iyer, D., Sampaziotis, F., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0197-9 · Cited by 195 · see citing works
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Longworth, J., Wu, D., Huete-Ortega, M., Wright, P. C., & Vaidyanathan, S. (2016) · Algal Research · doi:10.1016/j.algal.2016.06.015 · Cited by 127 · see citing works
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Schaffer, L. V., & Ideker, T. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.012 · Cited by 75 · see citing works
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Watanabe, S., Katsube, T., Hattori, H., Sato, H., Ishijima, T., Nakai, Y., Abe, K., & Sonomoto, K. (2013) · Journal of Bioscience and Bioengineering · doi:10.1016/j.jbiosc.2013.01.009 · Cited by 18 · see citing works
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Usluer, S., Galhuber, M., Khanna, Y., Bourgeois, B., Spreitzer, E., Michenthaler, H., Prokesch, A., & Madl, T. (2024) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2023.119654 · Cited by 9 · see citing works
- Authors
- Binns, D., Dimmer, E., Huntley, R., Barrell, D., O'Donovan, C., & Apweiler, R.
- Affiliations
- European Bioinformatics Institute (GB)
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
- Corresponding author
- Binns, David
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-09-10
- Volume
- 25
- Issue
- 22
- Pages
- 3045-3046
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC2773257
- OpenAlex
- W2168316093
- Cited by
- 971
- References
- 4
- Citations by year
- 2026: 66 · 2025: 78 · 2024: 92 · 2023: 84 · 2022: 80 · 2021: 98 · 2020: 57 · 2019: 63 · 2018: 63 · 2017: 58 · 2016: 53 · 2015: 49 · 2014: 46 · 2013: 32 · 2012: 30
- FWCI
- 6.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council (BB/E023541/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- Gene Ontology, gene ontology annotation, JavaScript, Ajax
- MeSH terms
- Software, User-Computer Interface, Databases, Factual, Information Storage and Retrieval, Computational Biology, Internet
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