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Data Visualization and Network Languages Applied to Heterogeneous Data in Bioinformatics

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International Journal of Computer Applications
© 2010 by IJCA Journal
Number 5 - Article 4
Year of Publication: 2010
Authors:
Bhavana.K
Umamaheswari.A
10.5120/128-244

Bhavana.k and Umamaheswari.A. Article: Data Visualization and Network languages applied to heterogeneous data in bioinformatics. International Journal of Computer Applications 1(5):26–32, February 2010. Published By Foundation of Computer Science. BibTeX

@article{key:article,
	author = {Bhavana.k and Umamaheswari.A},
	title = {Article: Data Visualization and Network languages applied to heterogeneous data in bioinformatics},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {1},
	number = {5},
	pages = {26--32},
	month = {February},
	note = {Published By Foundation of Computer Science}
}

Abstract

The analysis and interpretation of relationships between biological molecules, networks and concepts is becoming a major bottleneck in systems biology. Very often the pure amount of data and their heterogeneity provides a challenge for the visualization of the data. There are a wide variety of graph representations available, which most often map the data on 2D graphs to visualize biological interactions. These methods are applicable to a wide range of problems, nevertheless many of them reach a limit in terms of user friendliness when thousands of nodes and connections have to be analyzed and visualized. In this study we are reviewing visualization tools that are currently available for visualization of biological networks mainly invented in the latest past years. We comment on the functionality, the limitations and the specific strengths of these tools, and how these tools could be further developed in the direction of data integration and information sharing.

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