Figure 7
From: Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs
Evaluation of the backbone of the gene-disease-protein complex network. To evaluate the large-scale clustering we additionally included functional annotations. (a) and (b) compare the gene-complex backbone graph with the functional correlations of the extracted clusters according to FunCat annotation. Similarly, (d) and (e) show the gene-disease backbone and the clusters' disorder class correlations (see Methods). We see that interconnected clusters also seem to correlate in their annotations. To test this hypothesis rigorously, we calculated difference scores as defined in Methods in order to quantify the correlation of the backbones and their annotations, respectively. Vertical lines in (c) and (f) correspond to these difference scores for the fuzzy (black) and the hard (red) clustering. Comparing these values to the difference scores for 105 randomized cluster assignments we obtain significant p-values, both < 10-5. The correlations between annotations of connected clusters of the backbone is higher when applying the fuzzy approach.