Cell-to-cell communication in multicellular organisms is crucial to their development, controlling differentiation, and coordinating the activities of multiple cell types. Cell surface receptors and secreted ligands are a major mechanism by which cells communicate. An interaction map of the majority of likely cell-to-cell signalling paths between 144 cell types has been built (Ramilowski et al. Nat Comm, 2015); however, the structural properties of this cell-to-cell signalling network have not been investigated in depth. We will investigate the structural properties of this network and determine whether groups of highly interacting cells involved in common biological processes can be identified. We will also develop novel computational approaches to study these networks, including assessment of these approaches using synthetic datasets with known network structures. Once assessed, we will apply this methodology to the 144 primary human cell type network mentioned above to find underlying structures and cell communities. Lastly, cell-to-cell communication will be examined in single-cell datasets. We will adjust the proposed model to work with varying proportions of cells of different types and in different states. We will help answer very fundamental biological questions and provide the framework for studying communication between different cell types in medically relevant scenarios including autoimmunity and cancer.