Information content-based gene ontology functional similarity measures: which one to use for a given biological data type?

 

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dc.contributor.author Mazandu, Gaston K en_ZA
dc.contributor.author Mulder, Nicola J en_ZA
dc.date.accessioned 2015-12-28T06:47:48Z
dc.date.available 2015-12-28T06:47:48Z
dc.date.issued 2014 en_ZA
dc.identifier.citation Mazandu, G. K., & Mulder, N. J. (2014). Information content-based gene ontology functional similarity measures: which one to use for a given biological data type?. PloS one, 9(12), e113859. doi:10.1371/journal.pone.0113859 en_ZA
dc.identifier.uri http://hdl.handle.net/11427/16054
dc.identifier.uri http://dx.doi.org/10.1371/journal.pone.0113859
dc.description.abstract The current increase in Gene Ontology (GO) annotations of proteins in the existing genome databases and their use in different analyses have fostered the improvement of several biomedical and biological applications. To integrate this functional data into different analyses, several protein functional similarity measures based on GO term information content (IC) have been proposed and evaluated, especially in the context of annotation-based measures. In the case of topology-based measures, each approach was set with a specific functional similarity measure depending on its conception and applications for which it was designed. However, it is not clear whether a specific functional similarity measure associated with a given approach is the most appropriate, given a biological data set or an application, i.e., achieving the best performance compared to other functional similarity measures for the biological application under consideration. We show that, in general, a specific functional similarity measure often used with a given term IC or term semantic similarity approach is not always the best for different biological data and applications. We have conducted a performance evaluation of a number of different functional similarity measures using different types of biological data in order to infer the best functional similarity measure for each different term IC and semantic similarity approach. The comparisons of different protein functional similarity measures should help researchers choose the most appropriate measure for the biological application under consideration. en_ZA
dc.language.iso eng en_ZA
dc.publisher Public Library of Science en_ZA
dc.rights This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. en_ZA
dc.rights.uri http://creativecommons.org/licenses/by/4.0 en_ZA
dc.source PLoS One en_ZA
dc.source.uri http://journals.plos.org/plosone en_ZA
dc.subject.other Gene ontologies en_ZA
dc.subject.other Protein domains en_ZA
dc.subject.other Protein interaction networks en_ZA
dc.subject.other Protein-protein interactions en_ZA
dc.subject.other Gene ontology annotations en_ZA
dc.subject.other Semantics en_ZA
dc.subject.other Gene expression en_ZA
dc.subject.other Microarrays en_ZA
dc.title Information content-based gene ontology functional similarity measures: which one to use for a given biological data type? en_ZA
dc.type Journal Article en_ZA
dc.rights.holder © 2014 Mazandu, Mulder en_ZA
uct.type.publication Research en_ZA
uct.type.resource Article en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Health Sciences en_ZA
dc.publisher.department Institute of Infectious Disease and Molecular Medicine en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Mazandu, G. K., & Mulder, N. J. (2014). Information content-based gene ontology functional similarity measures: which one to use for a given biological data type?. <i>PLoS One</i>, http://hdl.handle.net/11427/16054 en_ZA
dc.identifier.chicagocitation Mazandu, Gaston K, and Nicola J Mulder "Information content-based gene ontology functional similarity measures: which one to use for a given biological data type?." <i>PLoS One</i> (2014) http://hdl.handle.net/11427/16054 en_ZA
dc.identifier.vancouvercitation Mazandu GK, Mulder NJ. Information content-based gene ontology functional similarity measures: which one to use for a given biological data type?. PLoS One. 2014; http://hdl.handle.net/11427/16054. en_ZA
dc.identifier.ris TY - Journal Article AU - Mazandu, Gaston K AU - Mulder, Nicola J AB - The current increase in Gene Ontology (GO) annotations of proteins in the existing genome databases and their use in different analyses have fostered the improvement of several biomedical and biological applications. To integrate this functional data into different analyses, several protein functional similarity measures based on GO term information content (IC) have been proposed and evaluated, especially in the context of annotation-based measures. In the case of topology-based measures, each approach was set with a specific functional similarity measure depending on its conception and applications for which it was designed. However, it is not clear whether a specific functional similarity measure associated with a given approach is the most appropriate, given a biological data set or an application, i.e., achieving the best performance compared to other functional similarity measures for the biological application under consideration. We show that, in general, a specific functional similarity measure often used with a given term IC or term semantic similarity approach is not always the best for different biological data and applications. We have conducted a performance evaluation of a number of different functional similarity measures using different types of biological data in order to infer the best functional similarity measure for each different term IC and semantic similarity approach. The comparisons of different protein functional similarity measures should help researchers choose the most appropriate measure for the biological application under consideration. DA - 2014 DB - OpenUCT DO - 10.1371/journal.pone.0113859 DP - University of Cape Town J1 - PLoS One LK - https://open.uct.ac.za PB - University of Cape Town PY - 2014 T1 - Information content-based gene ontology functional similarity measures: which one to use for a given biological data type? TI - Information content-based gene ontology functional similarity measures: which one to use for a given biological data type? UR - http://hdl.handle.net/11427/16054 ER - en_ZA


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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Except where otherwise noted, this item's license is described as This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.