Integrative networks combine multiple layers of biological data into a model of how genes work together to carry out cellular processes. Such networks become more valuable as they become more context specific, for example, by capturing how genes work together in a certain tissue or cell type. Once constructed, these networks provide the means to identify broad biological patterns underlying genes associated with complex traits and diseases. In this review, we discuss the different types of integrative networks that currently exist and how such networks that encompass multiple biological layers are constructed. We highlight how specificity can be incorporated into the reconstruction of different types of biomolecular interactions between genes, using tissue-specificity as a motivating example. We identify examples of cases where networks have been applied to study human diseases and discuss opportunities for new applications.