Abstract
DNA microarray is an innovative technology for obtaining information on gene function. Because it is a high-throughput method, computational tools are essential in data analysis and mining to extract the knowledge from experimental results. Filtering procedures and statistical approaches are frequently combined to identify differentially expressed genes. However, obtaining a list of differentially expressed genes is only the starting point because an important step is the integration of differential expression profiles in a biological context, which is a hot topic in data mining. In this chapter an integrated approach of filtering and statistical validation to select trustable differentially expressed genes is described together with a brief introduction on data mining focusing on the classification of co-regulated genes on the basis of their biological function.
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Saviozzi, S., Iazzetti, G., Caserta, E., Guffanti, A., Calogero, R.A. (2004). Microarray Data Analysis and Mining. In: Decler, J., Reischl, U. (eds) Molecular Diagnosis of Infectious Diseases. Methods in Molecular Medicine™, vol 94. Humana Press. https://doi.org/10.1385/1-59259-679-7:67
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DOI: https://doi.org/10.1385/1-59259-679-7:67
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