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. 2014 Sep 30;9(9):e108065. doi: 10.1371/journal.pone.0108065

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© 2014 Navarro et al

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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Diagram of the main steps of the CisMiner procedure. Given a set of TFBSs, the process starts by performing a fuzzy hierarchical clustering to obtain a set of closely located TFBSs. The result of this step is a fuzzy transactional database, which will then be mined by a Fuzzy Frequent Itemset Mining algorithm (Fuzzy Frequent-Pattern Tree) to obtain a set of frequent fuzzy itemsets. Finally, a postprocessing takes place in order to handle overlapping TFBSs that appear in each frequent itemset. As a result, a set of putative CRMs, along with their estimated p-value and their fuzzy support, is given.