Predicting Host-Pathogen Protein-Protein Interactions

Computational Biology

Protein-protein interactions are a key mechanism in cellular physiology and in pathogen infections of hosts — such as viral or bacterial diseases in humans. This project pushes the limit of machine learning methods on sparse data, including active learning and new transfer learning techniques, to predict host-pathogen interactomes. We leverage known interactions from better-studied pathogens to infer potential interactions in other less-well-studied ones, resulting in improved prediction accuracy.