Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
We address possible limitations of publicly available data sets of yeast gene expression. We study the predictability of known regulators via time-series analysis, and show that l...
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
Even after an experimentally prepared gene expression data set has been pre-processed to account for variations in the microarray technology, there may be inconsistencies between ...