Metabotyping using dynamic OMICs data
Dr. Jirstrand’s research covers learning dynamical systems, non-linear filtering, and time-series analysis (with applications in pharmacometrics, personalized nutrition, systems biology, and physiology). Furthermore, his group is active in artificial intelligence methods and applications such as deep neural networks, reinforcement learning; federated learning; and natural language processing. Recent work by his team is in mathematical modeling for personalized nutrition and includes algorithms for detecting groups of individuals who respond differently to the same diet (also known as metabotyping).