| 改进的非负矩阵因子分解算法在基因数据分析中的应用 |
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| 引用本文： | 张瑾,王加俊.改进的非负矩阵因子分解算法在基因数据分析中的应用[J].苏州大学学报(医学版),2008,24(4):45-48. |
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| 作者姓名： | 张瑾 王加俊 |
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| 作者单位： | [1]苏州大学电子信息学院,江苏苏州215021 [2]香港城市大学电子工程系,香港九龙852 |
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| 摘 要： | 提出一种改进的非负矩阵因子分解算法．在非负矩阵因子分解的迭代计算过程中加入了数据平滑处理来解决抖动问题，并用于一组白血病微阵列数据分析．实验结果表明，改进过的非负矩阵分解算法提高了分类的准确率，同时这个方法避免了NMF算法的“零值”问题．
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| 关 键 词： | 非负矩阵因子分解 平滑处理 白血病微阵列 基因数据分析 |
Improved non-negative factorization in the analysis of gene expression data |
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| Zhang Jin,Wang Jiajun.Improved non-negative factorization in the analysis of gene expression data[J].Journal of Suzhou University(Natural Science),2008,24(4):45-48. |
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| Authors: | Zhang Jin Wang Jiajun |
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| Institution: | Zhang Jin, Wang Jiajun( 1. School of Electronics and Information Engineering,Suzhou Univ.,Suzhou 215021 ,China; 2. Department of Electronic Engineering, City University of Hong Kong, Kowloon 852, China) |
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| Abstract: | Improvement non-negative matrix factorization （NMF） algorithm has been proposed. Data smoothing has been added in the iteration of the NMF algorithm to solve the dithering problem. The improved NMF algorithm is applied in the analysis of leukaemia microarray data. Experiment results show that the accuracy can be significantly improved with the proposed algorithm. Furthermore, the problem of ＇ zeros＇ for the traditional NMF algorithms can be easily tackled in our proposed method. |
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| Keywords: | non-negative matrix factorization smoothing leukaemia microarray gene data analysis |
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