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dc.contributor.authorLe Cao, K-A
dc.contributor.authorMeugnier, E
dc.contributor.authorMcLachlan, GJ
dc.date.accessioned2021-02-04T02:21:21Z
dc.date.available2021-02-04T02:21:21Z
dc.date.issued2010-05-01
dc.identifierpii: btq107
dc.identifier.citationLe Cao, K. -A., Meugnier, E. & McLachlan, G. J. (2010). Integrative mixture of experts to combine clinical factors and gene markers. BIOINFORMATICS, 26 (9), pp.1192-1198. https://doi.org/10.1093/bioinformatics/btq107.
dc.identifier.issn1367-4803
dc.identifier.urihttp://hdl.handle.net/11343/259651
dc.description.abstractMOTIVATION: Microarrays are being increasingly used in cancer research to better characterize and classify tumors by selecting marker genes. However, as very few of these genes have been validated as predictive biomarkers so far, it is mostly conventional clinical and pathological factors that are being used as prognostic indicators of clinical course. Combining clinical data with gene expression data may add valuable information, but it is a challenging task due to their categorical versus continuous characteristics. We have further developed the mixture of experts (ME) methodology, a promising approach to tackle complex non-linear problems. Several variants are proposed in integrative ME as well as the inclusion of various gene selection methods to select a hybrid signature. RESULTS: We show on three cancer studies that prediction accuracy can be improved when combining both types of variables. Furthermore, the selected genes were found to be of high relevance and can be considered as potential biomarkers for the prognostic selection of cancer therapy. AVAILABILITY: Integrative ME is implemented in the R package integrativeME (http://cran.r-project.org/).
dc.languageEnglish
dc.publisherOXFORD UNIV PRESS
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0
dc.titleIntegrative mixture of experts to combine clinical factors and gene markers
dc.typeJournal Article
dc.identifier.doi10.1093/bioinformatics/btq107
melbourne.affiliation.departmentSchool of Mathematics and Statistics
melbourne.affiliation.facultyScience
melbourne.source.titleBioinformatics
melbourne.source.volume26
melbourne.source.issue9
melbourne.source.pages1192-1198
dc.rights.licenseCC BY-NC
melbourne.elementsid1220044
melbourne.contributor.authorLe Cao, Kim-Anh
dc.identifier.eissn1460-2059
melbourne.accessrightsOpen Access


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