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Medusa: A tool for exploring and clustering biological networks
BACKGROUND: Biological processes such as metabolic pathways, gene regulation or protein-protein interactions are often represented as graphs in systems biology. The understanding of such networks, their analysis, and their visualization are today important challenges in life sciences. While a great...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3197509/ https://www.ncbi.nlm.nih.gov/pubmed/21978489 http://dx.doi.org/10.1186/1756-0500-4-384 |
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author | Pavlopoulos, Georgios A Hooper, Sean D Sifrim, Alejandro Schneider, Reinhard Aerts, Jan |
author_facet | Pavlopoulos, Georgios A Hooper, Sean D Sifrim, Alejandro Schneider, Reinhard Aerts, Jan |
author_sort | Pavlopoulos, Georgios A |
collection | PubMed |
description | BACKGROUND: Biological processes such as metabolic pathways, gene regulation or protein-protein interactions are often represented as graphs in systems biology. The understanding of such networks, their analysis, and their visualization are today important challenges in life sciences. While a great variety of visualization tools that try to address most of these challenges already exists, only few of them succeed to bridge the gap between visualization and network analysis. FINDINGS: Medusa is a powerful tool for visualization and clustering analysis of large-scale biological networks. It is highly interactive and it supports weighted and unweighted multi-edged directed and undirected graphs. It combines a variety of layouts and clustering methods for comprehensive views and advanced data analysis. Its main purpose is to integrate visualization and analysis of heterogeneous data from different sources into a single network. CONCLUSIONS: Medusa provides a concise visual tool, which is helpful for network analysis and interpretation. Medusa is offered both as a standalone application and as an applet written in Java. It can be found at: https://sites.google.com/site/medusa3visualization. |
format | Online Article Text |
id | pubmed-3197509 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31975092011-10-21 Medusa: A tool for exploring and clustering biological networks Pavlopoulos, Georgios A Hooper, Sean D Sifrim, Alejandro Schneider, Reinhard Aerts, Jan BMC Res Notes Technical Note BACKGROUND: Biological processes such as metabolic pathways, gene regulation or protein-protein interactions are often represented as graphs in systems biology. The understanding of such networks, their analysis, and their visualization are today important challenges in life sciences. While a great variety of visualization tools that try to address most of these challenges already exists, only few of them succeed to bridge the gap between visualization and network analysis. FINDINGS: Medusa is a powerful tool for visualization and clustering analysis of large-scale biological networks. It is highly interactive and it supports weighted and unweighted multi-edged directed and undirected graphs. It combines a variety of layouts and clustering methods for comprehensive views and advanced data analysis. Its main purpose is to integrate visualization and analysis of heterogeneous data from different sources into a single network. CONCLUSIONS: Medusa provides a concise visual tool, which is helpful for network analysis and interpretation. Medusa is offered both as a standalone application and as an applet written in Java. It can be found at: https://sites.google.com/site/medusa3visualization. BioMed Central 2011-10-06 /pmc/articles/PMC3197509/ /pubmed/21978489 http://dx.doi.org/10.1186/1756-0500-4-384 Text en Copyright ©2011 Pavlopoulos et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Note Pavlopoulos, Georgios A Hooper, Sean D Sifrim, Alejandro Schneider, Reinhard Aerts, Jan Medusa: A tool for exploring and clustering biological networks |
title | Medusa: A tool for exploring and clustering biological networks |
title_full | Medusa: A tool for exploring and clustering biological networks |
title_fullStr | Medusa: A tool for exploring and clustering biological networks |
title_full_unstemmed | Medusa: A tool for exploring and clustering biological networks |
title_short | Medusa: A tool for exploring and clustering biological networks |
title_sort | medusa: a tool for exploring and clustering biological networks |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3197509/ https://www.ncbi.nlm.nih.gov/pubmed/21978489 http://dx.doi.org/10.1186/1756-0500-4-384 |
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