Abstract
In complex diseases different genotypic perturbations of the cellular system often lead to the same phenotype. While characteristic genomic alterations in many cancers exist, other combinations of genomic perturbations potentially lead to the same disease, dysregulating important pathways of the cellular system. In this study, we developed novel computational methods to identify dysregulated pathways and their direct causes in individual patients or patient groups. Specifically, we introduced efficient and powerful graph theoretic algorithms to identify such dysregulated pathways and their causal genes and applied our methods to a large set of glioma specific molecular data.