| 基于Fiedler向量的基因表达谱数据分类方法 |
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| 引用本文： | 王年,庄振华,唐俊,苏亮亮. 基于Fiedler向量的基因表达谱数据分类方法[J]. 中国生物工程杂志, 2010, 30(12): 82-86 |
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| 作者姓名： | 王年 庄振华 唐俊 苏亮亮 |
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| 作者单位： | 安徽大学计算智能与信号处理教育部重点实验室 合肥 230039 |
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| 摘 要： | 尝试将一种基于图的Fiedler向量的聚类算法引入到基因表达谱数据的肿瘤分类中来。该方法将分属不同类的所有样本通过高斯权构造Laplace完全图,经SVD分解后获得Fiedler向量,利用各样本所对应的Fiedler向量分量的符号差异来进行基因表达谱数据的分类。通过模拟数据仿真实验和对白血病两个亚型(ALL与AML)及结肠癌真实数据实验,证明了这一方法的有效性。
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| 关 键 词： | 分类 Fiedler向量 基因表达数据 |
| 收稿时间： | 2010-07-12 |
| 修稿时间： | 2010-09-18 |
Classification of Gene Expression Data Based on Fiedler Vector |
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| WANG Nian,ZHUANG Zhen-hua,TANG Jun,SU Liang-liang. Classification of Gene Expression Data Based on Fiedler Vector[J]. China Biotechnology, 2010, 30(12): 82-86 |
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| Authors: | WANG Nian ZHUANG Zhen-hua TANG Jun SU Liang-liang |
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| Affiliation: | Education Ministry Key Laboratory of Intelligent Computing &; Signal Processing, Anhui University, Hefei 230039, China |
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| Abstract: | An algorithm for classification of gene expression data based on Fiedler Vector was proposed. Firstly, the Laplacian matrix of complete graph is constructed on all the different types of gene expression data. Then, the Fiedler Vector is obtained by the singular value decomposition of this Laplacian matrix. Finally, the samples are divided into two classes by utilizing the signs of the Fiedler Vector components. The effectiveness of this algorithm has been proven by simulation experiment and real data experiment. |
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| Keywords: | Classification Fiedler Vector Gene expression data |
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