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MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological 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 ap...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5260057/ https://www.ncbi.nlm.nih.gov/pubmed/28155725 http://dx.doi.org/10.1186/s12918-016-0363-3 |
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author | Truong, Cong-Doan Tran, Tien-Dzung Kwon, Yung-Keun |
author_facet | Truong, Cong-Doan Tran, Tien-Dzung Kwon, Yung-Keun |
author_sort | Truong, Cong-Doan |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0363-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5260057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52600572017-01-26 MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks Truong, Cong-Doan Tran, Tien-Dzung Kwon, Yung-Keun BMC Syst Biol Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0363-3) contains supplementary material, which is available to authorized users. BioMed Central 2016-12-23 /pmc/articles/PMC5260057/ /pubmed/28155725 http://dx.doi.org/10.1186/s12918-016-0363-3 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Truong, Cong-Doan Tran, Tien-Dzung Kwon, Yung-Keun MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks |
title | MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks |
title_full | MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks |
title_fullStr | MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks |
title_full_unstemmed | MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks |
title_short | MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks |
title_sort | moro: a cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5260057/ https://www.ncbi.nlm.nih.gov/pubmed/28155725 http://dx.doi.org/10.1186/s12918-016-0363-3 |
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