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Visual data mining of genomic databases by immersive graph-based exploration
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Source Computer graphics and interactive techniques in Australasia and South East Asia archive
Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia table of contents
Dunedin, New Zealand
SESSION: Interactive visualisation table of contents
Pages: 143 - 146  
Year of Publication: 2005
ISBN:1-59593-201-1
Authors
N. Férey  Université Paris SUD XI, Orsay (France)
P. E. Gros  Université Paris SUD XI, Orsay (France)
J. Hérisson  Université Paris SUD XI, Orsay (France)
R. Gherbi  Université Paris SUD XI, Orsay (France)
Sponsor
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
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ABSTRACT

Biologists are leading current research on genome characterization (sequencing, alignment, transcription), providing a huge quantity of raw data about many genome organisms. Extracting knowledge from this raw data is an important process for biologists, using usually data mining approaches. However, it is difficult to deals with these genomic information using actual bioinformatics data mining tools, because data are heterogeneous, huge in quantity and geographically distributed. In this paper, we present a new approach between data mining and virtual reality visualization, called visual data mining. Indeed Virtual Reality becomes ripe, with efficient display devices and intuitive interaction in an immersive context. Moreover, biologists use to work with 3D representation of their molecules, but in a desktop context. We present a software solution, Genome3DExplorer, which addresses the problem of genomic data visualization, of scene management and interaction. This solution is based on a well-adapted graphical and interaction paradigm, where local and global topological characteristics of data are easily visible, on the contrary to traditional genomic database browsers, always focused on the zoom and details level.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Eisen, M. B. Spellman, P. T. Brown, P. O. and Botstein, D. 1998. Cluster Analysis and Display of Genome-wide Expression Patterns. In proceedings of the National Academy of Sciences, of the USA, 95, 14863--14868.
 
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Eades, P. 1984. A Heuristic for Graph Drawing. Congressus Nutnerantiunt, 42, 149--160.
 
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Collaborative Colleagues:
N. Férey: colleagues
P. E. Gros: colleagues
J. Hérisson: colleagues
R. Gherbi: colleagues