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CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape
Comparative analysis of biological networks is a major problem in computational integrative systems biology. By computing the maximum common edge subgraph between a set of networks, one is able to detect conserved substructures between them and quantify their topological similarity. To aid such anal...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042825/ https://www.ncbi.nlm.nih.gov/pubmed/28731857 http://dx.doi.org/10.1515/jib-2017-0014 |
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author | Larsen, Simon J. Baumbach, Jan |
author_facet | Larsen, Simon J. Baumbach, Jan |
author_sort | Larsen, Simon J. |
collection | PubMed |
description | Comparative analysis of biological networks is a major problem in computational integrative systems biology. By computing the maximum common edge subgraph between a set of networks, one is able to detect conserved substructures between them and quantify their topological similarity. To aid such analyses we have developed CytoMCS, a Cytoscape app for computing inexact solutions to the maximum common edge subgraph problem for two or more graphs. Our algorithm uses an iterative local search heuristic for computing conserved subgraphs, optimizing a squared edge conservation score that is able to detect not only fully conserved edges but also partially conserved edges. It can be applied to any set of directed or undirected, simple graphs loaded as networks into Cytoscape, e.g. protein-protein interaction networks or gene regulatory networks. CytoMCS is available as a Cytoscape app at http://apps.cytoscape.org/apps/cytomcs. |
format | Online Article Text |
id | pubmed-6042825 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
spelling | pubmed-60428252019-01-28 CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape Larsen, Simon J. Baumbach, Jan J Integr Bioinform Research Articles Comparative analysis of biological networks is a major problem in computational integrative systems biology. By computing the maximum common edge subgraph between a set of networks, one is able to detect conserved substructures between them and quantify their topological similarity. To aid such analyses we have developed CytoMCS, a Cytoscape app for computing inexact solutions to the maximum common edge subgraph problem for two or more graphs. Our algorithm uses an iterative local search heuristic for computing conserved subgraphs, optimizing a squared edge conservation score that is able to detect not only fully conserved edges but also partially conserved edges. It can be applied to any set of directed or undirected, simple graphs loaded as networks into Cytoscape, e.g. protein-protein interaction networks or gene regulatory networks. CytoMCS is available as a Cytoscape app at http://apps.cytoscape.org/apps/cytomcs. De Gruyter 2017-07-21 /pmc/articles/PMC6042825/ /pubmed/28731857 http://dx.doi.org/10.1515/jib-2017-0014 Text en ©2017, Simon J Larsen et al., published by De Gruyter, Berlin/Boston http://creativecommons.org/licenses/by-nc-nd/3.0 This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. |
spellingShingle | Research Articles Larsen, Simon J. Baumbach, Jan CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape |
title | CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape |
title_full | CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape |
title_fullStr | CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape |
title_full_unstemmed | CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape |
title_short | CytoMCS: A Multiple Maximum Common Subgraph Detection Tool for Cytoscape |
title_sort | cytomcs: a multiple maximum common subgraph detection tool for cytoscape |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042825/ https://www.ncbi.nlm.nih.gov/pubmed/28731857 http://dx.doi.org/10.1515/jib-2017-0014 |
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