Research article: Sparse regularized discriminant analysis with application to microarrays

Authors:
Ran Li;Baolin Wu
Affiliations:
Division of Biostatistics, School of Public Health University of Minnesota, Minneapolis, MN 55455, USA;Division of Biostatistics, School of Public Health University of Minnesota, Minneapolis, MN 55455, USA
Venue:
Computational Biology and Chemistry
Year:
2012

Citing 3
Cited 0

The modified truncated SVD method for regularization in general form

SIAM Journal on Scientific and Statistical Computing
Random Forests

Machine Learning
Differential gene expression detection and sample classification using penalized linear regression models

Bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

For cancer prediction using large-scale gene expression data, it often helps to incorporate gene interactions in the model. However it is not straightforward to simultaneously select important genes while modeling gene interactions. Some heuristic approaches have been proposed in the literature. In this paper, we study a unified modeling approach based on the @?"1 penalized likelihood estimation that can simultaneously select important genes and model gene interactions. We will illustrate its competitive performance through simulation studies and applications to public microarray data.