Abstract

Microarray Gene Profile studies can assess the global patterns of thousands of genes under different varying conditions. It provides important insights about the underlying genetic causes for diseases, ultimately allowing the development of modern chemical entities as medical-kit drug candidates. The informatics analysis and integration of microarray gene expression pattern are difficult for understanding or interpretation of gene array features. In this paper, we discuss the deterministic computational analysis of: the identification of differentially expressed genes using statistical methods, the discovery of gene clusters, and the classification of biological samples using standard clustering and classification approaches.

Keyword

Microarray gene expression profiles; Computational analysis; Clustering and classification.

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