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Motivation: Clustering co-expressed genes usually requires the definition of 'distance' or 'similarity' between measured datasets, the most common choices being Pearson correlation or Euclidean distance. With the size of available datasets steadily increasing, it has become feasible to consider other, more general, definitions as well. One alternative, based on information theory, is the mutual information, providing a general measure of dependencies between variables. While the use of mutualdoi:10.1093/bioinformatics/18.suppl_2.s231 pmid:12386007 fatcat:otrfcc2gjjgzlgha4avq44ic3y