: 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...
Genomics is an important emerging scientific field that relies on meaningful data visualization as a key step in analysis. Specifically, most investigation of gene expression micr...
Matthew A. Hibbs, Grant Wallace, Maitreya J. Dunha...
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...