Little-Known Algorithm May Help Resolve Dimensionality Challenge of Array Analysis | GenomeWeb
An oft-cited challenge in analyzing microarray experiments is the so-called “extreme dimensionality” of the data that arises when tens of thousands of variables are interrogated across relatively few samples.
Researchers have developed an arsenal of clustering and classification methods to address this issue, and countless papers have been published on the subject with the goal of improving methods to correlate groups of samples with particular phenotypes of interest.

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