Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analys...

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Bibliographic Details
Main Authors: Enrico Glaab, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0039932&type=printable
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