A systems biological perspective on complex human diseases: Uncovering hidden relations via multi-scale network analyses.

The identification of the underlying causes of complex diseases is one of the major challenges medical research is facing today. By considering complex systems from different perspectives, systems biology allows revealing novel insights into the molecular basis of diseases and therefore contributes to a more dynamic comprehension. For this, algorithms capable to analyze complex systems and methods which allow to find missing pieces in the complicated puzzle of understanding complex disease are necessary. The objective of this thesis was to address both by approaching complex systems via multi-scale network analyses and thereby allowing focusing on them from different perspectives in a systems-biological fashion. By yielding experimentally testable hypotheses about potential causative explanations, both together represent pieces in the puzzle of understanding complex diseases and strategies to solve it, and consequently they allow narrowing down the gap between genotype and phenotype