Each module is represented by a single group node whose radius is proportional to the number of nodes belonging to the module. c- d Results of the brief visualization mode with absolute and relative relations, respectively. We found a total of 16 modules each of which is represented by a circular list of genes. b Result of the detailed visualization mode. Modularity and robustness results in module and network levels are listed in the upper and the lower tables, respectively. Our app can be a promising tool which efficiently analyzes the relationship between modularity and robustness in large signaling networks.Д«oolean network Centrality Cytoscape app Gene-ontology Modularity Network robustness OpenCL Parallel computation.ДЄnalysis results of the STKE network by MORO. We tested the proposed app to analyze large signaling networks and showed an interesting relationship between network modularity and robustness. The app provides various visualization modes to better elucidate topological relations between modules, and tabular results of centrality and gene ontology enrichment analyses of modules.

A batch-mode simulation function was also developed to verify whether an observed relationship between modularity and robustness is conserved in a large set of randomly structured networks. In particular, to ensure the robustness algorithm's applicability to large-scale networks, we implemented it as a parallel algorithm by using the OpenCL library. We employed an existing algorithm to analyze the modularity of directed graphs and a Boolean network model for robustness calculation. Although there have been many studies revealing that dynamic robustness of a biological network is related to its modularity characteristics, no proper tool exists to investigate the relation between network dynamics and modularity.ДЄccordingly, we developed a novel Cytoscape app called MORO, which can conveniently analyze the relationship between network modularity and robustness.

Cytoscape huge networks