We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Background: Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation...
Gunnar Schramm, Marc Zapatka, Roland Eils, Rainer ...
Association rules can reveal biological relevant relationship between genes and environments / categories. However, most existing association rule mining algorithms are rendered i...
The recent development of microarray gene expression techniques have made it possible to offer phenotype classification of many diseases. However, in gene expression data analysis...
Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measu...
Nicola Neretti, Daniel Remondini, Marc Tatar, John...