Medusa: A tool for exploring and clustering biological networksReport as inadecuate

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BMC Research Notes

, 4:384

First Online: 06 October 2011Received: 31 May 2011Accepted: 06 October 2011DOI: 10.1186-1756-0500-4-384

Cite this article as: Pavlopoulos, G.A., Hooper, S.D., Sifrim, A. et al. BMC Res Notes 2011 4: 384. doi:10.1186-1756-0500-4-384


BackgroundBiological 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.

FindingsMedusa 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.

ConclusionsMedusa 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:

Keywordsgraph visualization biological networks clustering analysis data integration Electronic supplementary materialThe online version of this article doi:10.1186-1756-0500-4-384 contains supplementary material, which is available to authorized users.

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Author: Georgios A Pavlopoulos - Sean D Hooper - Alejandro Sifrim - Reinhard Schneider - Jan Aerts



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