We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
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: One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We wo...
Koji Kadota, Jiazhen Ye, Yuji Nakai, Tohru Terada,...
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Background: Microarray co-expression signatures are an important tool for studying gene function and relations between genes. In addition to genuine biological co-expression, corr...