Protein interactions can be represented using networks. Accordingly, approaches that have been developed in network science are appropriate for the analysis of protein interactions, and they can lead to the detection of new drug targets. Thus far, only ordinary ("monolayer") protein interaction networks have been exploited for drug discovery. However, because "multilayer networks" allow the representation of multiple types of interactions and of time-dependent interactions, they have the potential to improve insight from network-based approaches [1]. <br> Aim of my PhD project is firstly to employ multilayer methods on well-established data to investigate potential use cases of multilayer protein interaction networks. For example, we can find time-resolved groups of proteins that show similar activity during inflammation [2]. Ultimately, we explore the integration of data sets from multiple sources to draw more solid insights on a biological system than monolayer approaches. <br><br> References:<br> [1] Kivelä, Mikko, et al. "Multilayer networks." Journal of Complex Networks (2014)<br> [2] Calvano, Steve E., et al. "A network-based analysis of systemic inflammation in humans." Nature (2005)