FABIAN THEIS
Lab Profile
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.
- Manifold learning and stochastic processes for mapping high-dimensional data
-
Neural networks for imaging sequence data and – since recently – count data
-
Scaling established data analysis algorithms to millions of observations and thousands of dimensions
-
Bridging mechanistic and data-driven models
-
Network biology for multi-omics data
Institution Name
Institute of Computational Biology, Helmholtz Zentrum München
Institution Short Name
ICB, HMGU
Institution Address
Ingolstädter Landstr. 1, 85764 Neuherberg, Munich, Germany
Institution Website
Team
Principal Investigator
Fabian Theis
Director of ICB, Head of Machine Learning GroupProfessor at Technical University of Munich
