High-throughput protein-protein interaction data are becoming a foundation for new biological discoveries. A major challenge is to manage, analyze, and model these data. In this unit several databases are described that are used to store, query, and visualize protein-protein interaction data. Comparison between experimental techniques reveals that each high-throughput technique has its limitations in detecting certain types of interactions; however, the techniques are generally complementary. In silico prediction methods for protein-protein interactions can expand the scope of experimental data and increase the confidence of certain interactions. Use of protein-protein interaction networks, preferably integrating them with other types of data, allows assignment of cellular functions to novel proteins and derivation of new biological pathways. As demonstrated in this unit, bioinformatics can be used to transform protein-protein interaction data from noisy information into knowledge of cellular mechanisms.