A system of cluster analyses for gene expression signatures from cDNA microarrays is described to diagnose athletes` physiological conditions in response to training loads, which uses standard statistical algorithms to arrange altered genes according to similarity in the patterns of gene expression. The output is displayed graphically using heat maps and dendrograms, conveying the clustering and the underlying patterns of gene expression in a form intuitive for coaches. A "39-gene" model is developed to diagnose athletes` physiological conditions with cDNA microarrays. Since the pattern seen in gene expression signatures indicates the status of cellular processes, our results suggest a strategy to "see" training -induced cellular processes based on all of the 39 altered genes with cDNA microarrays.
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