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- Title
Bayesian model averaging: development of an improved multi-class, gene selection and classification tool for microarray data.
- Authors
Yeung, Ka Yee; Bumgarner, Roger E; Raftery, Adrian E
- Abstract
Selecting a small number of relevant genes for accurate classification of samples is essential for the development of diagnostic tests. We present the Bayesian model averaging (BMA) method for gene selection and classification of microarray data. Typical gene selection and classification procedures ignore model uncertainty and use a single set of relevant genes (model) to predict the class. BMA accounts for the uncertainty about the best set to choose by averaging over multiple models (sets of potentially overlapping relevant genes).
- Publication
Bioinformatics (Oxford, England), 2005, Vol 21, Issue 10, p2394
- ISSN
1367-4803
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/bti319