Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
: This paper addresses the sparse data problem in the linear regression model, namely the number of variables is significantly larger than the number of the data points for regress...
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
Background: Normalization is essential in dual-labelled microarray data analysis to remove nonbiological variations and systematic biases. Many normalization methods have been use...
Huiling Xiong, Dapeng Zhang, Christopher J. Martyn...