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
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Neural networks for imaging sequence data and – since recently – count data
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Scaling established data analysis algorithms to millions of observations and thousands of dimensions
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Bridging mechanistic and data-driven models
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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
