Modelling cellular communication networks to understand the regulatory drivers of disease

This thesis addresses the challenge of identifying the regulatory drivers of disease through the construction of cellular communication networks from single-cell RNA-sequencing data. The primary objective is to develop a method that identifies intercellular signals by examining intracellular effects, achieving a robust understanding of signaling pathways. Our results demonstrate the successful development of a method that not only performs well but also effectively combines prior knowledge with de novo approaches. Future research will aim to explore more dynamic modelling approaches, further enhancing the practical applications of this method in drug development and cellular biology