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The objective of this work “Biclustering Analysis on Class Discovery from Gene Expression Data”s, is to analysis biclustering techniques of data mining to create new algorithm and to improve the existing algorithm in order to apply them to some of the issues in Gene Expression Data such as Class Discovery to minimize the complexities involved in providing solutions to them. In this work an algorithm...
The clustering of genes detected as significant or differentially expressed provides useful information to biologists about functions and functional relationship of genes. There are variant types of clustering methods that can be applied in genomic data. These are mainly divided into the two groups, namely, hierarchical and partitional methods. In this paper, as the novelty, we perform a detailed...
Many existing clustering algorithms have been used to identify coexpressed genes in gene expression data. These algorithms are used mainly to partition data in the sense that each gene is allowed to belong only to one cluster. Since proteins typically interact with different groups of proteins in order to serve different biological roles, the genes that produce these proteins are therefore expected...
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