Spectral Methods for Cancer Classification using Microarray Data

被引：3
|
作者：
Kim, Saejoon [1 ]
机构：
[1] Sogang Univ, Dept Comp Sci & Engn, Seoul 121742, South Korea
来源：
INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL SCIENCES AND OPTIMIZATION, VOL 1, PROCEEDINGS | 2009年
关键词：
GENE; PREDICTION; PATTERNS;
D O I：
10.1109/CSO.2009.389
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper we present a novel method based on spectral bipartitioning, traditionally used for finding min-cuts in graphs, for classification of cancer using microarray data. Our method is applied to five publicly available datasets of acute leukemia, colon cancer ovarian cancer prostate cancer and diffuse large B-cell lymphoma, and is shown to have classification accuracy comparable to that of some of the currently known best classification methods for microarray data.
引用
收藏
页码：588 / 592
页数：5
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