Weshow that simple scoring functions can assign statistically signi scores to biologically relevant pathways. The basic idea is to generate biologically possible pathways and to score them with respect to gene expression measurements. We assess the signi cance of the scores for the investigated pathways by comparison to number of scores for random pathways. This suggests that the combination of appropriate scoring functions with the systematic generation of pathways can be used in order to select the interesting pathways based on gene expression measurements.. We present new approach fortheevaluation of gene expression data.

We suggest sample scoring functions for di erent problem speci cations. The basic idea is to generate biologically possible pathways and to score them with respect to gene expression measurements. Weshow that simple scoring functions can assign statistically signi scores to biologically relevant pathways. This suggests that the combination of appropriate scoring functions with the systematic generation of pathways can be used in order to select the interesting pathways based on gene expression measurements.. We present new approach fortheevaluation of gene expression data.
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