MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks

Abstract

BackgroundAlthough 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.ResultsAccordingly, we developed a novel Cytoscape app called MORO, which can conveniently analyze the relationship between network modularity and robustness. We employed an existing algorithm to analyze the modularity of directed graphs and a Boolean network model for robustness calculation. 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. 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. 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. We tested the proposed app to analyze large signaling networks and showed an interesting relationship between network modularity and robustness.ConclusionsOur app can be a promising tool which efficiently analyzes the relationship between modularity and robustness in large signaling networks.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0363-3) contains supplementary material, which is available to authorized users.

Density-dependent oxylipin production in natural diatom communities: possible implications for plankton dynamics

“…To better investigate the possible role of LOFAs as possible chemical factors modulating diatom–diatom links, co-variations of cell abundances were inspected, and data gathered therein were integrated by means of network analysis. As a preliminary step, consecutive weeks characterized by the persistence of the same water mass over time at LTER-MC were identified on the basis of salinity values [53]. Seven successive weeks ( N = 7) were therefore selected in February–March, while 3 weeks ( N = 3) were identified in each of 3 additional months (i.e.…”

Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks

“…Figure 2 (d) shows the trend of the correlation coefficient values between the changes of modularity and robustness values against the removal rate, and we observed that they were significantly negative irrespective of the removal rates (see Additional file 1 : Figure S1 (d) and S2 (d) for the results of STF and HIV-1 networks, respectively). Actually, the negative relationship between the modularity and the robustness in signaling networks was observed in our previous studies [ 18 , 19 ]. However, it should be noted that the previous finding does not imply any relation between the changes of the modularity and the robustness by edge-removal mutations.…”

“…In this study, we examined the modularity by using the method in a previous study [ 25 ] and it has been widely used in many previous studies [ 18 , 19 , 26 , 27 ]. Given a directed graph G ( V , A ) where V and A denote a set of nodes and a set of directed edges, respectively, we consider a partition P = { V 1 , V 2 , …, V M } of V (i.e.…”

“…We need to extensively simulate randomly structure networks to verify that the new findings in real networks are generally conserved. In this study, we employed a shuffling model to generate random networks [ 10 , 18 ]. Given a reference network, it rewires some edges in a way that in-degree and out-degree of every node are conserved.…”

“…In metabolic networks, the robustness against the mutant concentrations of metabolites or the mutant expression of enzymes has increased or decreased, respectively, as the modularity increases [ 17 ]. On the other hand, the robustness against a gene state perturbation was negatively correlated with the modularity in signaling networks [ 18 , 19 ]. Although these previous studies found interesting relations between the robustness and the modularity, there are some issues needed to be investigated as follows.…”