DocumentCode :
2972560
Title :
Equalized orthogonal map-based DNA microarray data analysis for cancer diagnosis
Author :
Patra, Jagdish C. ; Detpongsante, Sineepong ; Meher, Pramod K. ; Ang, Ee Luang
Author_Institution :
Nanyang Technol. Univ., Singapore
fYear :
2007
fDate :
10-13 Dec. 2007
Firstpage :
1
Lastpage :
5
Abstract :
A new approach to cancer diagnosis involves the analysis of gene expression data. However, to make sense of multidimensional DNA microarray data is a challenging task. Beyond 3 dimensions, it is very difficult for humans to make intuitive interpretation of how each data point is distributed, how they are interrelated, and how they should be categorized. Equalized orthogonal map (EOM), an approach to dimension reduction was able to produce topologically correct mappings for visualization and classification of cancer types. Performance comparison with a self-organizing map (SOM) is also discussed. Experimental results show that EOM performs well with DNA microarray data classification.
Keywords :
DNA; cancer; medical diagnostic computing; self-organising feature maps; cancer diagnosis; equalized orthogonal map; multidimensional DNA microarray data analysis; self-organizing map; Cancer; DNA; Data analysis; Data visualization; Gene expression; Medical treatment; Multidimensional systems; Pattern recognition; Principal component analysis; Topology; Cancer classification; dimension reduction mapping; neural networks; visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Communications & Signal Processing, 2007 6th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-0982-2
Electronic_ISBN :
978-1-4244-0983-9
Type :
conf
DOI :
10.1109/ICICS.2007.4449625
Filename :
4449625
Link To Document :
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