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

Abstract

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.

DOI: 10.1109/ICMLA.2008.25

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Cite this paper

@article{Song2008ClusteringFD, title={Clustering for DNA Microarray Data Analysis with a Graph Cut Based Algorithm}, author={Jia Feng Song and Chunmei Liu and Yinglei Song and Junfeng Qu}, journal={2008 Seventh International Conference on Machine Learning and Applications}, year={2008}, pages={595-598} }