Recent growth in protein-protein interaction (PPI) data provides massive opportunities for gaining biological insights, including the characterization of protein complexes and pathways. Many tools and resources exist to analyse and disseminate these data, but often bench scientists are not trained in them. In particular, they need to learn how to explore, manage, and interconnect these datasets. Given the importance of such techniques in several biomedical science disciplines, there is a major need for training in relevant tools without which bench scientists risk missing important insights from their own data. This EMBO Practical Course aims to train participants in bioinformatics techniques for gaining a network perspective on PPIs, predicting and analysing them, highlighting differences between globular (protein "domains") and non-globular (intrinsically disordered peptide) modules, and working with large datasets. Ideal participants for this course are bench scientists who are working to obtain data related to protein-protein interactions, or already have such data they want to analyse. One of the focuses of this course will be teaching the importance of PPIs in biological systems, and how bioinformatics tools can be harnessed for understanding and controlling physiological states and when these states are perturbed by disease. Keeping these aspects into consideration, disease datasets are integrated into the training materials. We will teach state-of-the-art bioinformatics tools, including Cytoscape, STRING, ELM, IUPRED and Chimera2. We will focus on integrating experimental interaction data (XL-MS, Bio-ID) into PPI networks. Many of the publicly available tools are highly interconnected and we will show participants how to take advantage of this integration.