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Analysis of Gene Expression Data with Pathway Scores

机译:途径评分的基因表达数据分析

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We present a new approach for the evaluation of gene expression data. The basic idea is to generate biologically possible pathways and to score them with respect to gene expression measurements. We suggest sample scoring functions for different problem specifications. We assess the significance of the scores for the investigated path-ways by comparison to a number of scores for random pathways. We show that simple scoring functions can assign statistically significant 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 most interesting pathways based on gene expression measurements.
机译:我们提出了一种评估基因表达数据的新方法。基本思想是产生生物学上可能的途径并对它们相对于基因表达测量进行评分。我们建议不同问题规范的样本评分功能。我们通过比较随机途径的许多分数来评估所研究的路径方式的分数的重要性。我们表明,简单的评分功能可以为生物相关的途径分配统计上大量的分数。这表明可以使用具有系统产生的适当评分功能的组合,以便基于基因表达测量选择最有趣的途径。

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