Information content-based gene ontology semantic similarity approaches: toward a unified framework theory

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dc.contributor.authorMazandu, Gaston K
dc.contributor.authorMulder, Nicola J
dc.date.accessioned2021-10-08T06:20:17Z
dc.date.available2021-10-08T06:20:17Z
dc.date.issued2013
dc.description.abstractSeveral approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG). These approaches contributed to improving protein analyses at the functional level. Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches. We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures. We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric. Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration. This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches. The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term’s specificity in the GO DAG.
dc.identifier.apacitationMazandu, G. K., & Mulder, N. J. (2013). Information content-based gene ontology semantic similarity approaches: toward a unified framework theory. <i>BioMed Research International</i>, 2013(4), 174 - 177. http://hdl.handle.net/11427/34241en_ZA
dc.identifier.chicagocitationMazandu, Gaston K, and Nicola J Mulder "Information content-based gene ontology semantic similarity approaches: toward a unified framework theory." <i>BioMed Research International</i> 2013, 4. (2013): 174 - 177. http://hdl.handle.net/11427/34241en_ZA
dc.identifier.citationMazandu, G.K. & Mulder, N.J. 2013. Information content-based gene ontology semantic similarity approaches: toward a unified framework theory. <i>BioMed Research International.</i> 2013(4):174 - 177. http://hdl.handle.net/11427/34241en_ZA
dc.identifier.issn2314-6133
dc.identifier.issn2314-6141
dc.identifier.ris TY - Journal Article AU - Mazandu, Gaston K AU - Mulder, Nicola J AB - Several approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG). These approaches contributed to improving protein analyses at the functional level. Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches. We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures. We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric. Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration. This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches. The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term’s specificity in the GO DAG. DA - 2013 DB - OpenUCT DP - University of Cape Town IS - 4 J1 - BioMed Research International LK - https://open.uct.ac.za PY - 2013 SM - 2314-6133 SM - 2314-6141 T1 - Information content-based gene ontology semantic similarity approaches: toward a unified framework theory TI - Information content-based gene ontology semantic similarity approaches: toward a unified framework theory UR - http://hdl.handle.net/11427/34241 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/34241
dc.identifier.vancouvercitationMazandu GK, Mulder NJ. Information content-based gene ontology semantic similarity approaches: toward a unified framework theory. BioMed Research International. 2013;2013(4):174 - 177. http://hdl.handle.net/11427/34241.en_ZA
dc.language.isoeng
dc.publisher.departmentComputational Biology Division
dc.publisher.facultyFaculty of Health Sciences
dc.sourceBioMed Research International
dc.source.journalissue4
dc.source.journalvolume2013
dc.source.pagination174 - 177
dc.source.urihttps://dx.doi.org/10.1155/2013/292063
dc.subject.otherdirected acyclic graph
dc.subject.otherinformation content
dc.subject.othersemantic similarity scores
dc.subject.othergene ontology
dc.subject.otherunified framework
dc.titleInformation content-based gene ontology semantic similarity approaches: toward a unified framework theory
dc.typeJournal Article
uct.type.publicationResearch
uct.type.resourceJournal Article
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