The genomic era has been characterised by vast amounts of data from diverse sources, creating a need for new tools to extract biologically meaningful information. Bioinformatics is, for the most part, responding to that need. The sparseness of the genomic data associated with diseases, however, creates a new challenge. Understanding the complex interplay between genes and proteins requires integration of data from a wide variety of sources, i.e. gene expression, genetic linkage, protein interaction, and protein structure among others. Thus, computational tools have become critical for the integration, representation and visualization of heterogeneous biomedical data. Furthermore, several bioinformatics methods have been developed to formulate predictions about the functional role of genes and proteins, including their role in diseases. After an introduction to the complex interplay between proteins and genetic diseases, this review explores recent approaches to the understanding of the mechanisms of disease at the molecular level. Finally, because most known mechanisms leading to disease involve some form of protein interaction, this review focuses on the recent methodologies for understanding diseases through their underlying protein interactions. Recent contributions from genetics, protein structure and protein interaction network analyses to the understanding of diseases are discussed here.