Information content-based gene ontology functional similarity measures: which one to use for a given biological data type?
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.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.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.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.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 |
dc.identifier.uri | http://hdl.handle.net/11427/16054 | |
dc.identifier.uri | http://dx.doi.org/10.1371/journal.pone.0113859 | |
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.language.iso | eng | en_ZA |
dc.publisher | Public Library of Science | en_ZA |
dc.publisher.department | Institute of Infectious Disease and Molecular Medicine | en_ZA |
dc.publisher.faculty | Faculty of Health Sciences | en_ZA |
dc.publisher.institution | University of Cape Town | |
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.holder | © 2014 Mazandu, Mulder | 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 |
uct.type.filetype | Text | |
uct.type.filetype | Image | |
uct.type.publication | Research | en_ZA |
uct.type.resource | Article | en_ZA |
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