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非负矩阵分解及其在基因表达数据分析中的应用 被引量：13

NON-NEGATIVE MATRIX FACTORIZATION AND ITS APPLICATIONS TO GENE EXPRESSION DATA ANALYSIS
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摘要 介绍非负矩阵分解的基本原理及其在生物信息学中基因表达数据分析中的应用.并将该方法用于一组白血病微阵列数据的聚类,得到了新的结果. Non-negative matrix factorization （NMF） is a data analysis novelty rappidly developping in recent years. As an understandable and easily executing method, NMF has been widely used in a variaty of areas. The basic mathematical theory of NMF and its applications to gene expression data analysis are briefly introduced, then it is used to the clustering of a leukaemia microarray data set and some new results are obtained.
作者 曹胜玉 刘来福
机构地区 北京师范大学数学科学学院
出处 《北京师范大学学报（自然科学版）》 CAS CSCD 北大核心 2007年第1期30-33,共4页 Journal of Beijing Normal University(Natural Science)
关键词 非负矩阵分解 生物信息学 基因芯片 DNA微阵列 NMF bioinformatics Gene-Chip DNA microarray
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献12

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同被引文献153

引证文献13

二级引证文献35

北京师范大学学报（自然科学版）
2007年 第1期

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