Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/102691
Title: A new clustering method for microarray data analysis.
Authors: Zhang, L. 
Zhu, S.
Issue Date: 2002
Source: Zhang, L.,Zhu, S. (2002). A new clustering method for microarray data analysis.. Proc IEEE Comput Soc Bioinform Conf 1 : 268-275. ScholarBank@NUS Repository.
Abstract: A novel clustering approach is introduced to overcome data missing and inconsistency of gene expression levels under different conditions in the stage of clustering. It is based on the so-called smooth score, which is defined for measuring the deviation of the expression level of a gene and the average expression level of all the genes involved under a condition. We present an efficient greedy algorithm for finding clusters with smooth score below a threshold after studying its computational complexity. The algorithm was tested intensively on random matrixes and a yeast data. It was shown to perform well in finding co-regulation patterns in a test with the yeast data.
Source Title: Proc IEEE Comput Soc Bioinform Conf
URI: http://scholarbank.nus.edu.sg/handle/10635/102691
ISSN: 15553930
Appears in Collections:Staff Publications

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