| 模糊C-均值聚类分析在基因表达数据分析中的应用 |
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| 引用本文： | 陈佳妮,段文英,丁徽.模糊C-均值聚类分析在基因表达数据分析中的应用[J].森林工程,2010,26(2):54-57,76. |
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| 作者姓名： | 陈佳妮 段文英 丁徽 |
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| 作者单位： | 东北林业大学,哈尔滨,150040 |
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| 摘 要： | 为更好地挖掘基因表达数据、获取更多的生物学信息，近年来许多改进的传统聚类算法和新聚类算法不断涌现。模糊聚类在聚类分析中又具有广泛的意义和重要的应用价值。叙述基因表达数据的获取和表达，介绍应用在基因表达数据中的模糊C均值聚类算法以及不同的实现途径和相应的优缺点，简述聚类结果的评价问题，并对发展趋势做进一步的展望。
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| 关 键 词： | DNA微阵列 基因表达数据 聚类分析 |
Application of Fuzzy C-means Clustering Analysis in Gene Expression Data Analysis |
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| Chen Jiani,Duan Wenying,Ding Hui.Application of Fuzzy C-means Clustering Analysis in Gene Expression Data Analysis[J].Forest Engineering,2010,26(2):54-57,76. |
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| Authors: | Chen Jiani Duan Wenying Ding Hui |
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| Institution: | Chen Jiani,Duan Wenying,Ding Hui(Northeast Forestry University,Harbin 150040) |
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| Abstract: | In order to better analyze the gene expression data and obtain more biological information,many improved traditional clustering algorithms and new clustering algorithms have emerged continually in recent years.The fuzzy clustering has a widespread significance and important application value in the clustering analysis.The acquisition and expression of gene data were firstly introduced,then the fuzzy C-means clustering method applied in gene expression data and the different realized approaches were mainly d... |
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| Keywords: | DNA microarray gene expression data clustering analysis |
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