文章基本信息

标题：An Improved Correlation Measure-based SOM Clustering Algorithm for Gene Selection
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作者：Xu, Jiucheng ; Xu, Tianhe ; Sun, Lin 等
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2013
卷号：8
期号：12
页码：3082-3087
DOI：10.4304/jsw.8.12.3082-3087
语种：English
出版社：Academy Publisher
摘要：Among the large amount of genes presented in microarray gene expression data, only a small fraction of them is effective for performing a certain diagnostic test. For this reason, reducing the dimensionality of gene expression data is imperative. Self-organizing map (SOM) is a type of mathematical cluster analysis which particularly well suited for recognizing and classifying features in complex, multidimensional data. This paper proposes an improved Self-organizing map clustering algorithm which based on neighborhood mutual information correlation measure. To evaluate the performance of the proposed approach, we apply it to six well-known gene expression datasets and compare our results with those obtained by other methods. Finally, the experimental results show that the proposed approach to gene selection is indeed efficient.
关键词：self-organizing map; neighborhood mutual information;correlation measure;clustering algorithm