Systematic deciphering of protein-protein interactions has the potential to generate comprehensive and instructive signaling networks and to fuel new therapeutic and diagnostic strategies. Here, we describe how recent advances in high-throughput proteomic technologies, involving biochemical purification methods and mass spectrometry analysis, can be applied systematically to the characterization of protein complexes and the computation of molecular networks. The networks obtained form the basis for further functional analyses, such as knockdown by RNA interference, ultimately leading to the identification of nodes that represent candidate targets for pharmacological exploitation. No individual experimental approach can accurately elucidate all critical modulatory components and biological aspects of a signaling network. Such functionally annotated protein-protein interaction networks, however, represent an ideal platform for the integration of additional datasets. By providing links between molecules, they also provide links to all previous observations associated with these molecules, be they of genetic, pharmacological, or other origin. As exemplified here by the analysis of the tumor necrosis factor (TNF)-alpha/nuclear factor-kappaB (NF-kappaB) signaling pathway, the approach is applicable to any mammalian cellular signaling pathway in the immune system.