Statistical methods for analyzing data from DNA microarray experiments are reviewed. Specifically, we discuss common experimental setups, methods for data reduction and clustering, and analysis of time-course experiments. While early microarray studies focused mainly on the basic methodological and technical aspects of DNA arrays, emphasis has shifted to biological, medical, and clinical applications. We mention several of these and present results from our recent research as illustrative examples. New developments in this ever-growing field are outlined.
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