Protein interactions mediate essentially all biological processes and analysis of protein-protein interactions has contributed fundamental insights to the understanding of biological systems. In recent years, interactome network maps have emerged as an important tool for analyzing and interpreting genetic data of complex phenotypes. The long-term goal of INET - Institute of Network Biology - is to understand how macromolecular networks control biological processes and how networks evolve in response to exogenous, microbial and endogenous factors as well as evolutionary processes. Protein interaction networks To ensure survival and reproductive success all organisms need to continuously integrate information on environmental conditions with internal programs into appropriate physiological responses. This is done by complex networks of proteins and other macromolecules that are poorly understood on a systems level. The goal of my group is to map and functionally understand the principles underlying biological networks using Arabidopsis thaliana as a model. The long-term objective is to understand and predict how perturbation by natural genetic variation or experimental manipulation causes phenotype. Large-scale network mapping: High-quality maps are a prerequisite for studying biological networks. We use state-of-the-art experimental protein interaction analysis based on the yeast-2-hybrid system and other assays to build proteome-scale interaction network maps of increasing quality and completeness. These maps are analyzed using biological inspection, applying tools of network science such as community detection, and by integrating protein interactions with other functional data, e.g. transcriptomics (Arabidopsis Interactome Mapping Consortium, Science 2011). Biological modules: Several projects aim at in-depth characterizing important modules that are central to plant development and survival: phytohormone signaling and pathogen-host interactions. To understand how signals that provide information on different environmental variables are integrated on a molecular level we are constructing a phytohormone signaling network (PhyHormNet). To understand how pathogens perturb the host network we have previously constructed a first plant-pathogen interactome network (PPIN-1). We found that evolutionary diverse pathogens converge on few, highly-connected proteins, so-called hubs, in the Arabidopsis network. For >90% (17/18) of the host proteins targeted by two pathogens a role in immunity could be demonstrated in subsequent genetic validation experiments. However the biological reason why these are targeted by pathogens is unknown and currently investigated Functional characterization: An important question in interactome analysis is the possible direction of causal effects for each interaction, i.e. which interaction partner regulates the other. This is also critical information for reconstruction of information flow through networks. To explore the function and directionality of novel interactions, we develop functional assays for specific protein groups and high-confidence candidates.