DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures

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dc.contributor.authorMazandu, Gastonen_ZA
dc.contributor.authorMulder, Nicolaen_ZA
dc.date.accessioned2015-11-23T11:44:12Z
dc.date.available2015-11-23T11:44:12Z
dc.date.issued2013en_ZA
dc.description.abstractBACKGROUND: The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. RESULTS: We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. CONCLUSIONS: The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.en_ZA
dc.identifier.apacitationMazandu, G., & Mulder, N. (2013). DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures. <i>BMC Bioinformatics</i>, http://hdl.handle.net/11427/15243en_ZA
dc.identifier.chicagocitationMazandu, Gaston, and Nicola Mulder "DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures." <i>BMC Bioinformatics</i> (2013) http://hdl.handle.net/11427/15243en_ZA
dc.identifier.citationMazandu, G. K., & Mulder, N. J. (2013). DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures. BMC bioinformatics, 14(1), 284.en_ZA
dc.identifier.ris TY - Journal Article AU - Mazandu, Gaston AU - Mulder, Nicola AB - BACKGROUND: The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. RESULTS: We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. CONCLUSIONS: The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis. DA - 2013 DB - OpenUCT DO - 10.1186/1471-2105-14-284 DP - University of Cape Town J1 - BMC Bioinformatics LK - https://open.uct.ac.za PB - University of Cape Town PY - 2013 T1 - DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures TI - DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures UR - http://hdl.handle.net/11427/15243 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/15243
dc.identifier.urihttp://dx.doi.org/10.1186/1471-2105-14-284
dc.identifier.vancouvercitationMazandu G, Mulder N. DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures. BMC Bioinformatics. 2013; http://hdl.handle.net/11427/15243.en_ZA
dc.language.isoengen_ZA
dc.publisherBioMed Central Ltden_ZA
dc.publisher.departmentInstitute of Infectious Disease and Molecular Medicineen_ZA
dc.publisher.facultyFaculty of Health Sciencesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Licenseen_ZA
dc.rights.holder2013 Mazandu and Mulder; licensee BioMed Central Ltd.en_ZA
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_ZA
dc.sourceBMC Bioinformaticsen_ZA
dc.source.urihttp://www.biomedcentral.com/bmcbioinformatics/en_ZA
dc.subject.otherOntology (GO) dataen_ZA
dc.subject.otherprotein analysesen_ZA
dc.subject.otherDaGO-Funen_ZA
dc.titleDaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measuresen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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