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Clustering for DNA Microarray Data Analysis with a Graph Cut Based Algorithm

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4 Author(s)
Jia Song ; Coll. of Electr. Eng., Zhejiang Univ., China ; Chunmei Liu ; Yinglei Song ; Junfeng Qu

Clustering is an important approach to the analysis of DNA microarray data. In this paper, we develop a new algorithm that can cluster DNA microarray data with a graph cut based algorithm. The algorithm can generate a list of clustering results with statistically significant likelihood. It can thus resolve the issue where a gene product may participate in different subsets of co-expressed genes. Our testing results on two biological sets showed that this approach can achieve improved clustering accuracy, compared with other clustering methods.

Published in:

Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on

Date of Conference:

11-13 Dec. 2008