Cong-Doan Truong1, Tien-Dzung Tran2, Yung-Keun Kwon3. 1. Department of IT Convergence, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 680-749, Republic of Korea. 2. Complex Network and Bioinformatics Group, Center for Research and Development, Hanoi University of Industry, Hanoi, Vietnam. 3. Department of IT Convergence, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 680-749, Republic of Korea. kwonyk@ulsan.ac.kr.
Abstract
BACKGROUND: 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. RESULTS: Accordingly, 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. CONCLUSIONS: Our app can be a promising tool which efficiently analyzes the relationship between modularity and robustness in large signaling networks.
BACKGROUND: 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. RESULTS: Accordingly, 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. CONCLUSIONS: Our app can be a promising tool which efficiently analyzes the relationship between modularity and robustness in large signaling networks.
Authors: John H Morris; Leonard Apeltsin; Aaron M Newman; Jan Baumbach; Tobias Wittkop; Gang Su; Gary D Bader; Thomas E Ferrin Journal: BMC Bioinformatics Date: 2011-11-09 Impact factor: 3.307
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