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Research Article Open Access
Gene expression mining has been effectively used for classification and diagnosis of cancer. This paper highlights traditional approaches as well as current advancements in the analysis of the gene expression data from cancer perspective. Analysis of such data is important as it leads to knowledge discovery. However, mining data in a centralized system can cause a difficulty in execution. So we are proposing a distributed approach which can improve the performance by reducing the overhead. The distributed approach exploits parallel computation by splitting the entire process among a number of systems.
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Author(s): Cisy Soman, Abdul Ali
Data mining, gene expression data, clustering, association rules, cancer, Autonomic and Context Aware Computing,Bioinformatics and Computational Biology,Broadband and Intelligent Networks,Calm Technology,CDMA/GSM Communication Protocol