Protein-protein interaction networks have been used since the early days of systems biology to model functional relationships between genes and proteins. On the computational side, they have been immensely helpful for de novo network enrichment strategies that could uncover novel disease modules as potential mechanisms or as a source of biomarkers and drug targets. In recent years, it has become clear though that protein-protein interaction networks have limits, e.g. due to literature and experimental bias as well as lack of cell-type or tissue-specificity that also affects the results of network enrichment methods that rely on them. Widely available next-generation sequencing data nowadays offers the possibility to refine these networks to account for context-specific changes that reflect cell-type, tissue-, disease-specific or even individual variations of the global interactome. Information about domain-domain interactions and alternative splicing can be used to refine protein-protein interaction networks. I will present our database DIGGER as well as the functional enrichment tool NEASE which together offer unique insights into alternative splicing changes on a network level.