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Data Visualization and Network Languages Applied to Heterogeneous Data in Bioinformatics

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 5 - Article 4
Year of Publication: 2010

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

	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}


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.


    [1 ] S, Doerks T, Krüger B, Snel B, Bork P: STRING7 recent developments in the Integration and prediction Proteinteractions. Nucleic Acids Res 200635(D358-62)
    [2] Kuhn M, von Mering C, Campillos M, Jensen LJ,Bork P: STITCH: interaction networks of chemicals and proteins. NucleicAcids Res 2008,(36 Database): D684-688. [Shannon P,
    [3] Ramage D, Amin N,Schwikowski B, Ideker T:Cytoscape: a software Environment for Integrated models of biomol ecular interaction networks. Genome Res 2003, 13(11):2498-2504.
    [4] Freeman TC, Goldovsky L, Brosch M, van Dongen Enright AJ:Construction, visualization, and clustering of Transcription networks from microarray expression data. PLoS computational biology 2007,3(10):2032-2042.
    [5] Breitkreutz : Osprey: a network visualization system.
    [6] The BioGrid Iragne F, Nikolski M, Mathieu B, Auber D, Sherman D:ProViz: protein interaction visualization and exploration. Bioinformatics 2005, 21(2):272-274.
    [7] Auber D: Tulip: A huge graph visualization framework. Mathematics and Visualization 200 105-126
    [8] Frick A, Ludwig A, Mehldan H: A fast adaptive layout algorithm for undirected graphs. Proceedings of Workshop on Graph Drawing 94,LNCS 1994, (894):389-403.
    [9] Hermjakob Apweiler R: The HUPO PSI's molecular interaction format – a community standard for the representation of protein interaction data. Nat Biotechnology 2004,22(2):177-183.
    [10] Hermjakob H, Montecchi-Palazzi L, Lewington C, Intact: an open source molecular interaction database Nucleic Acids Res 2004, (32 Database):D452-455.
    [11] Köhler J, Rawlings C, Verrier P, Mitchell R, Skusa A Rüegg A, Philippi S: Linking experimental results, biological networks and sequence analysis methods using Ontology’s and Generalized Data Structures.
    [12] Köhler JB, Graph-based analysis and visualization of experimental results with ONDEX. Bioinformatics 2006, 22(11):1383-1390.
    [13] Skusa A, Rüegg A, Köhler J:Extraction of biological networks from scientific literature. Briefings in Bioinformatics 2005.