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 webcite.
%0 Journal Article
%1 Pavlopoulos2011Medusa
%A Pavlopoulos, Georgios
%A Hooper, Sean
%A Sifrim, Alejandro
%A Schneider, Reinhard
%A Aerts, Jan
%D 2011
%J BMC Research Notes
%K networks tool visualisation
%N 1
%P 384+
%R 10.1186/1756-0500-4-384
%T Medusa: A tool for exploring and clustering biological networks
%U http://dx.doi.org/10.1186/1756-0500-4-384
%V 4
%X 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 webcite.
@article{Pavlopoulos2011Medusa,
abstract = {{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 webcite.},
added-at = {2018-12-02T16:09:07.000+0100},
author = {Pavlopoulos, Georgios and Hooper, Sean and Sifrim, Alejandro and Schneider, Reinhard and Aerts, Jan},
biburl = {https://www.bibsonomy.org/bibtex/2aab109d63c0078afd77776dd7386dab2/karthikraman},
citeulike-article-id = {10119148},
citeulike-linkout-0 = {http://dx.doi.org/10.1186/1756-0500-4-384},
citeulike-linkout-1 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3197509/},
citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/21978489},
citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=21978489},
doi = {10.1186/1756-0500-4-384},
interhash = {9a21195822424c2c3404a19f113f9d1e},
intrahash = {aab109d63c0078afd77776dd7386dab2},
issn = {1756-0500},
journal = {BMC Research Notes},
keywords = {networks tool visualisation},
number = 1,
pages = {384+},
pmcid = {PMC3197509},
pmid = {21978489},
posted-at = {2011-12-12 10:22:44},
priority = {2},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {Medusa: A tool for exploring and clustering biological networks},
url = {http://dx.doi.org/10.1186/1756-0500-4-384},
volume = 4,
year = 2011
}