A new clustering method for microarray data analysis

被引：13

作者：

Zhang, LX ^{[1
]}

Zhu, S ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Math & LIT, Singapore 117543, Singapore

来源：

CSB2002: IEEE COMPUTER SOCIETY BIOINFORMATICS CONFERENCE | 2002年

关键词：

D O I：

10.1109/CSB.2002.1039349

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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 it-ell in finding co-regulation patterns in a test with the yeast data.

引用

页码：268 / 275

页数：8

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