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Each value in the simulated graph is an average over 1,000 Monte Carlo simulations.
We use simulated graph data with cluster structures as used in [36, 38 40].
The simulated graph is generated using the Erdos-Renyi model [24] with some modifications to generate clusters.
The simulated graph is a weakly connected directed graph generated using R package bnlearn ([ 40]).
We first show the performance of the LRW algorithm using simulated graph data.
The experiments using simulated graph data were repeated 10 times and the average NMI scores and the average number of clusters are reported.
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These graphs, and almost all real-world graphs, are more heterogeneous than the simulated graphs G1, G2 and G3.
Two simulated graphs are shown in Fig. 1, where the clusters are colored differently and the graphs are visualized by force-directed algorithms.
The results obtained are similar to the performances recorded on simulated graphs.
Since the simulated graphs with overlapping communities might not faithfully reflect the biological reality (i.e. proteins may be involved in more than two processes), we verified that multiclustered nodes in simulated and biological graphs have similar characteristics.
Finally, we show that our method outperforms other existing methods (Adamcsek et al., 2006; Ahn et al., 2010) both on simulated graphs and on PPI networks.
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