Principal component analysis based unsupervised feature extraction applied to budding yeast temporally periodic gene expression

Volume: 9, Issue: 1, Pages: 22 - 22
Published: Jun 29, 2016
Abstract
Background The recently proposed principal component analysis (PCA) based unsupervised feature extraction (FE) has successfully been applied to various bioinformatics problems ranging from biomarker identification to the screening of disease causing genes using gene expression/epigenetic profiles. However, the conditions required for its successful use and the mechanisms involved in how it outperforms other supervised methods is unknown,...
Paper Details
Title
Principal component analysis based unsupervised feature extraction applied to budding yeast temporally periodic gene expression
Published Date
Jun 29, 2016
Volume
9
Issue
1
Pages
22 - 22
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