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Published on: May 4, 2018
A survey of visualization tools for biological network analysis.
Georgios A Pavlopoulos1, Anna-Lynn Wegener, Reinhard Schneider
1Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, Heidelberg, Germany. pavlopou@embl.de
Biodata Mining
|December 2, 2008
Summary
Analyzing complex biological networks is challenging due to data volume and heterogeneity. This review examines recent visualization tools for biological networks, highlighting their strengths and limitations for improved data integration.
Area of Science:
- Systems biology
- Bioinformatics
- Computational biology
Background:
- Analyzing relationships between biological molecules, networks, and concepts presents a significant bottleneck in systems biology.
- Data heterogeneity and sheer volume pose challenges for effective visualization of biological data.
- Current 2D graph representations for biological interactions often become user-unfriendly with large datasets (thousands of nodes and connections).
Purpose of the Study:
- To review recently developed visualization tools for biological networks.
- To assess the functionality, limitations, and strengths of these tools.
- To suggest future development directions for enhanced data integration and information sharing.
Main Methods:
- Literature review of recent visualization tools for biological networks.
- Analysis of tool functionality, limitations, and strengths.
- Qualitative assessment of user-friendliness for large-scale network visualization.
Main Results:
- A range of visualization tools exist, primarily developed in recent years.
- Existing tools vary in their effectiveness, user-friendliness, and suitability for large biological networks.
- Many tools struggle with the scalability required for analyzing thousands of nodes and connections.
Conclusions:
- There is a need for improved visualization tools in systems biology to handle complex and heterogeneous data.
- Future development should focus on enhancing data integration and information sharing capabilities of these tools.
- Optimizing user-friendliness for large-scale biological network analysis remains a critical challenge.
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