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Roman Baptista, Xia Dong, Laura Toni (4 Royal College St, London NW1 0TU)
Protein-protein interactions (PPIs) underlie most cellular functions, determining outcomes of infection and therapeutic responses through pathogen interaction with hubs and bottlenecks of the host PPI network. Modelling PPIs as graph-based networks allows us to study this phenomenon on irregular (non-Euclidean) but structured geometry. Graph-based machine learning allows inference and exploitation of structure for PPI prediction, specifically the ability to predict sequential actions of key biomarkers. This project will generate a host-pathogen interactome map for coccidiosis, a disease caused by Eimeria with annual economic impact on global poultry production exceeding €2 billion. Current vaccines are sub-optimal and new subunit vaccines are required. Our network will leverage multi-dimensional data from existing PPI literature, time-series gene expression, and abundant functional annotations for host/parasite genomes. The model generated will significantly advance our ability to identify vaccine targets and utilize host networks to optimize responses.https://www.rvc.ac.uk/about/our-people/dong-xia#tab-research