Proteins play a versatile role in nearly all biological processes, and dysregulation of protein functions often leads to disease. It is therefore crucial to understand the unique and distinct features of these biological processes, and the proteins that form their constituent parts.
However, proteins do not work alone. Rather, they associate in a variety of ways with many other proteins to perform their function. Several different types of such protein associations are known, including direct protein-protein interaction, protein complex formation, and (coordinated) participation in the same metabolic or signaling pathway. However, current protein association
studies tend to be biased towards the detection of binary protein-protein interactions. As a result, all types of protein association tend to be poorly analyzed. This is an important gap in our knowledge, as these other association types also play a crucial role in biology, and their absence
thus hampers our understanding of many biological processes. This project therefore builds on the Tabloid Proteome, a protein association detection method and corresponding online resource (http://www.tabloidproteome.com) to improve and extend our ability to detect such protein associations, and to mine the resulting network for biological knowledge related to health and
disease.