Background: Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test-...
Xing Qiu, Andrew I. Brooks, Lev Klebanov, Andrei Y...
Background: Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, ...
Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...
Alexander L. Richards, Peter Holmans, Michael C. O...
Background: ChIP-chip data, which indicate binding of transcription factors (TFs) to DNA regions in vivo, are widely used to reconstruct transcriptional regulatory networks. Howev...
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...