EDISA: extracting biclusters from multiple time-series of gene expression profiles

  title={EDISA: extracting biclusters from multiple time-series of gene expression profiles},
  author={Jochen Supper and Martin Strauch and Dierk Wanke and Klaus Harter and Andreas Zell},
  journal={BMC Bioinformatics},
  pages={334 - 334}
Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consisting of co-regulated genes. A growing pool of publicly available microarray datasets allows the identification of modules by monitoring expression changes over time. These time-series datasets can be searched for gene expression modules by one of the many clustering methods published to date. For an integrative analysis, several time… CONTINUE READING
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