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Conference Paper

Analysis of Gene Expression Data with Pathway Scores

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84331

Zien,  A
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Zien, A., Küffner R, Zimmer, R., & Lengauer, T. (2000). Analysis of Gene Expression Data with Pathway Scores. Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology (ISMB 2000), 407-417.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-E481-1
Abstract
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. The significance of the scores for the investigated pathways is assessed 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.