【摘 要】
：
Clustering gene expression profiles is important to construeting gene regulatory networks.We consider the problem of clustering short time-course microarray
【机 构】
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Washington University in St.Louis St.Louis, Missouri, USA
【出 处】
：
The Third IMS-China International Conference on Statistics a
论文部分内容阅读
Clustering gene expression profiles is important to construeting gene regulatory networks.We consider the problem of clustering short time-course microarray data.Direct applications of traditional clustering methods often ignore the temporal ordering of the gene expressions, We instead define candidate gene clusters using the order restriction profiles over the mean expression across time, and convert the clustering problem to a model selection problem.
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