Microarrays provide the biological research community with tremendously rich, sensitive and detailed information on gene expression profiles. Gene expression profiling and gene expression patterns have been found useful for solving a wide variety of important biological and biomedical problems, including the study of metabolic pathways, inference of the functions of unknown genes, diagnosis of diseased states, as well as facilitating the development of individualized drug treatments through pharmacogenomics. Given the significant impact of microarray gene expression data in biological and biomedical research, this breakthrough technology urgently needs the assistance of advanced computational methods for interpreting and utilizing the raw information. This paper reviews several main research directions and methods in the analysis of microarray gene expression data.
Keywords: Microarrays, gene expression, data analysis, image processing, signal processing, pattern classification, machine learning, computational techniques
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