Gene expression data clustering based on local similarity combination

被引:0
|
作者
Pan, D [1 ]
Wang, F [1 ]
机构
[1] Fudan Univ, Dept Comp Sci & Engn, Shanghai 200433, Peoples R China
来源
PROCEEDINGS OF THE 4TH ASIA-PACIFIC BIOINFORMATICS CONFERENCE | 2006年 / 3卷
关键词
D O I
10.1142/9781860947292_0038
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Clustering is widely used in gene expression analysis, which helps to group genes with similar biological function together. The traditional clustering techniques are not suitable to be directly applied to gene expression time series data, because of the inhered properties of local regulation and time shift. In order to cope with the existing problems, the local similarity and time shift, we have developed a new similarity measurement technique called Local Similarity Combination in this paper. And at last, we'll run our method on the real gene expression data and show that it works well.
引用
收藏
页码:353 / 362
页数:10
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