Elucidating mechanisms of life requires analysis of whole systems and understanding the complex interplay of the individual components. Proteins control and mediate the majority of biological activities and interactions among proteins play a decisive role in the dynamic modulation of cellular behavior. Protein-protein interactions are essential constituents of all cells and interactome analysis is an important component in the quest for a systems level understanding of life. Using a high-quality binary interactome mapping pipeline we explore interactome networks for yeast, human and plant at ever increasing completeness and quality. Based on benchmarking and standardized reference sets combined experimental approaches and mathematical modelling are used to ensure quality and asses the completeness of interactome maps. These models enable a critical assessment of current maps and guide development of a roadmap towards completion. We recently completed mapping of the first binary interactome network for the reference plant Arabidopsis thaliana. Using tools of graph theory we identify biologically relevant network communities from which a picture of the overall interactome network organization starts to emerge. Combination of interaction and comparative genomics data yielded insights into network evolution, and biological inspection resulted in many hypotheses for unknown proteins and revealed unexpected connectivity between previously studied components of phytohormone signaling pathways.Lastly, it was investigated how viral, bacterial and fungal pathogens perturb their host’s network. For plants it was found that pathogen effectors from evolutionary distant pathogens converge on network hubs, which appear “guarded” by resistance proteins, and which are functionally important for the host’s immune responses. Together, it will be shown how high-quality protein interactome network maps provide us with tools for elucidating fundamental laws underlying biological systems that need to be analyzed using both experimental and computational approaches.