Spectral pattern comparison methods for cancer classification based on microarray gene expression data

被引：6
|
作者：
Pham, Tuan D. [1 ]
Beck, Dominik
Yan, Hong
机构：
[1] James Cook Univ N Queensland, Bioinformat Applicat Res Ctr, Townsville, Qld 4811, Australia
[2] James Cook Univ N Queensland, Sch Informat Technol, Townsville, Qld 4811, Australia
[3] City Univ Hong Kong, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China
[4] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia
来源：
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS | 2006年 / 53卷 / 11期
关键词：
classification; feature selection; microarrays; spectral distortions; vector quantization;
D O I：
10.1109/TCSI.2006.884407
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We present, in this paper, two spectral pattern comparison methods for cancer classification using microarray gene expression data. The proposed methods are different from other current classifiers in the ways features are selected and pattern similarities measured. In addition, these spectral methods do not require any data preprocessing which is neccessary for many other classification techniques. Expertimental results using three popular microarray data sets demonstrate the robustness and effectiveness of the spectral pattern classifiers.
引用
收藏
页码：2425 / 2430
页数：6
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