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Performing clustering analysis is one of the important research topics in cancer discovery using gene expression profiles, which is crucial in facilitating the successful diagnosis and treatment of cancer. While there are quite a number of research works which perform tumor clustering, few of them considers how to incorporate fuzzy theory together with an optimization process into a consensus clustering...
Cluster analysis is an important tool for discovering the structures and patterns hidden in gene expression data. In this paper, a new algorithm for clustering gene expression profiles is proposed. In this method, we find natural clusters in the data based on a competitive learning strategy. Using partially known modes as constraints in our method, we reduce the sensitivity of the clustering procedure...
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