Machine Learning group, ICB
Coming from a focus on network biology and mechanistic modeling, the machine learning group evolved to a focus for data driven modeling of mostly single-cell transcriptomic data. This includes manifold learning and stochastic processes for mapping high-dimensional, non-linear data. Often, these techniques are combined with neural-network-based representations of these data. At the same time, the group continues to apply and develop statistical and differential equation-based model to gain insight into the role of specific variables in these data. We collaborate with various experimental groups with applications from stem cell biology, differentiation to disease modeling.