Integrative mixture of experts to combine clinical factors and gene markers

Le Cao, Kim-Anh, Meugnier, Emmanuelle and McLachlan, Geoffrey J. (2010) Integrative mixture of experts to combine clinical factors and gene markers. Bioinformatics, 26 9: 1192-1198. doi:10.1093/bioinformatics/btq107


Author Le Cao, Kim-Anh
Meugnier, Emmanuelle
McLachlan, Geoffrey J.
Title Integrative mixture of experts to combine clinical factors and gene markers
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4803
1367-4811
Publication date 2010-05
Sub-type Article (original research)
DOI 10.1093/bioinformatics/btq107
Volume 26
Issue 9
Start page 1192
End page 1198
Total pages 7
Editor Alex Bateman
Alfonso Valencia
Place of publication Oxford, U.K.
Publisher Oxford University Press
Collection year 2011
Language eng
Subject 0104 Statistics
06 Biological Sciences
Formatted abstract
Motivation: 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/). Contact: k.lecao@uq.edu.au. Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2010. Published by Oxford University Press.

Keyword Breast-Cancer
Prostate Carcinoma
Expression
Classification
Apoptosis
Chemotherapy
Progression
Extension
Networks
Cells
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
Institute for Molecular Bioscience - Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
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Created: Sun, 16 May 2010, 00:07:53 EST