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58 Gonye et al.Fig. 3. A network visualization of a Feasnet that is filtered based on overrepresentationof transcriptional regulatory elements. Rectangular boxes represent the TREs andthe elliptical boxes represent the promoters (colored based on the Gene ClusterMembership Data). A high-resolution color version of the gray-scale image presentedherein is available online at http://www.dbi.tju.edu/dbi/publications/MiMBchapter/.The FeasnetViewer module contains various functions for the visualization andanalysis of a Feasnet. An image of the interaction matrix is produced in which theindividual elements of the matrix are represented by a color based on the significancevalues for that particular TRE (p-values for overrepresentation in theobserved Feasnet). This module also contains functionality for hierarchical clusteringusing “R” software for statistical analysis (http://www.r-project.org). For clustering,the pair-wise distance that is most appropriate for the Feasnet data is thebinary distance. The binary distance between two genes (or TF) can be computed,as the ratio of number of elements for which the two rows (or columns) are dissimilarto the total number of elements for which either of the rows contains a one. Forthe genes, binary distance is the “dissimilarity” between the regulatory pattern oftwo genes as related to the total number of distinct binding sites present on either ofthem. For the TF, binary distance is the “dissimilarity” between the regulatory patternsof two TF as related to the total number of genes regulated by either of the TF.