Measuring gene similarity by means of the classification distance
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.