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Microarray Data Classification Using Support Vector Machine
Full text
International Journal of Biometrics and Bioinformatics (IJBB)
Table of Contents
Download Complete Issue    PDF(1.41MB)
Volume:  5    Issue:  1
Pages:  1-27
Publication Date:   March / April 2011
ISSN (Online): 1985-2347
10 - 15
Seeja K.R. - India
Shweta - India
Published Date   
CSC Journals, Kuala Lumpur, Malaysia
Keywords   Abstract   References   Cited by   Related Articles   Collaborative Colleague
KEYWORDS:   Support Vector Machines, Microarray, Classification 
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DNA microarrays allow biologist to measure the expression of thousands of genes simultaneously on a small chip. These microarrays generate huge amount of data and new methods are needed to analyse them. In this paper, a new classification method based on support vector machine is proposed. The proposed method is used to classify gene expression data recorded on DNA microarrays. It is found that the proposed method is faster than neural network and the classification performance is not less than neural network. 
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14 WEKA software:
1 D. A. Salem, R. A. Abul Seoud and H. A. Ali, (2011), “DMCA: A Combined Data Mining Technique for Improving the Microarray Data Classification Accuracy” in Proceedings of International Conference on Environment and BioScience, IPCBEE vol.21 (2011) © (2011) IACSIT Press, Singapore, 2011, pp. 36-41.
2 D. A. Salem, R. A. Abul and H. A. Ali, “MGS-CM: A Multiple Scoring Gene Selection Technique for Cancer Classification using Microarrays”, International Journal of Computer Applications, 36(6), pp. 30-37. December 2011.
3 D. A. Salem, R. A. A. A. Abul Seoud, and H. A. Ali, “A New Gene Selection Technique Based on Hybrid Methods for Cancer Classification Using Microarrays”, International Journal of Bioscience, Biochemistry and Bioinformatics, 1(4), pp. 261-266. November 2011.
Seeja K.R. : Colleagues
Shweta : Colleagues  
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