Universität Rostock, 2019
Abstract: I propose an integrative workflow to study large-scale biochemical networks by combining omics data, network structure and dynamical analysis to unravel disease mechanisms. Using the workflow, I identified core regulatory networks from the E2F1 network underlying EMT in bladder and breast cancer and detected disease signatures and drug targets, which were experimentally validated. Further, I developed a hybrid modeling framework that combines ODE- with logical-models to analyze the dynamics of large-scale non-linear systems. This thesis is a contribution to interdisciplinary cancer research.
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