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Figure 2 | BMC Bioinformatics

Figure 2

From: MINE: Module Identification in Networks

Figure 2

Modularity vs. Cluster Size and Geometric Accuracy at Optimal Settings. for each algorithm, we selected the setting with the optimal balance of modularity and average geometric accuracy for the C. elegans interactome from WI8 based on GO Cellular Component annotations. The boxplot, below, represents the global modularity of the clusters (x-axis) vs. A) the distribution of cluster sizes (y-axis) and B) the distribution of the geometric accuracy (y-axis). The circle indicates the median value; thick lines indicate upper and lower quartiles; whiskers indicate 1.5 times the inter-quartile range (IQR). The total number of clusters identified by each algorithm is indicated in parentheses in the key. A) The plot shows that MINE produces clusters of varying sizes while maintaining a higher overall modularity. B) The plot shows that MINE produces clusters with a much higher overall modularity and a similar range of geometric accuracy as other algorithms without producing an artificially large number of clusters.

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