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- Title
Comparative evaluation of set-level techniques in predictive classification of gene expression samples.
- Authors
Holec, Matěj; Kléma, Jiří; Zelezný, Filip; Tolar, Jakub
- Abstract
Analysis of gene expression data in terms of a priori-defined gene sets has recently received significant attention as this approach typically yields more compact and interpretable results than those produced by traditional methods that rely on individual genes. The set-level strategy can also be adopted with similar benefits in predictive classification tasks accomplished with machine learning algorithms. Initial studies into the predictive performance of set-level classifiers have yielded rather controversial results. The goal of this study is to provide a more conclusive evaluation by testing various components of the set-level framework within a large collection of machine learning experiments.
- Publication
BMC bioinformatics, 2012, Vol 13 Suppl 10, pS15
- ISSN
1471-2105
- Publication type
Journal Article
- DOI
10.1186/1471-2105-13-S10-S15