CDNA microarrays curse or blessing

The biggest challenge for scientists confronted with gene expression data is the biological interpretation of large datasets. With the development of microarray technologies, biological sciences experienced an exponential leap from a paradigm where one experiment involves one or two measurements in a known area to a new paradigm where one experiment provides data on thousands of measurements often involving genes for which the scientist may have very little familiarity. This demands a new form of abstract thinking from the scientists involved - new principles are developing as to how to approach these data sets most efficiently. Scientists need to achieve both the ability for grasping the big picture provided by the gene expression changes and to focus on the truly novel insights in the data sets. At this point, traditional biological follow-up studies are necessary to test the biological hypotheses developed from the gene expression analysis. This is both a challenge and an opportunity: while it was never before possible to learn so much from a single experiment, it was also never before so difficult to extract meaningful information from the results of a single experiment.

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