Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...
Background: Spatially mapped large scale gene expression databases enable quantitative comparison of data measurements across genes, anatomy, and phenotype. In most ongoing effort...
Christopher Lau, Lydia Ng, Carol Thompson, Sayan D...
Background: The biological information in genomic expression data can be understood, and computationally extracted, in the context of systems of interacting molecules. The automat...
Bruz Marzolf, Eric W. Deutsch, Patrick Moss, David...