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We aim at elucidating the composition of heterogeneous cell populations and how these implement function in the context of cancer and immune biology by jointly evaluating single cell and genome wide measurements. Read more

Group News


Eirini's paper accepted in Nature Communications

Sensitive detection of rare disease-associated cell subsets via representation learning. Using CellCnn, we identify paracrine signaling-, AIDS onset- and rare CMV infection-associated cell subsets in peripheral blood, and extremely rare leukemic blast populations in minimal residual disease-like situations with frequencies as low as 0.01%. Read more 


Claassen Group: Postdoctoral researcher position: single cell transcriptomics time series models for personalized medicine.

The Claassen group at the Institute for Molecular Systems Biology, ETH Zurich is offering a position for a postdoctoral researcher in computational single cell biology Read more 


Anna's paper accepted in PLOS Computational Biology.

Sparse Regression Based Structure Learning of Stochastic Reaction Networks from Single Cell Snapshot Time Series Read more 


Justins' paper came out in Cell Systems

Analysis of Cell Lineage Trees by Exact Bayesian Inference Identifies Negative Autoregulation of Nanog in Mouse Embryonic Stem Cells Read more 


Claassen Lab Semester Project: Deep Learning for dynamic system motif detection in health and disease

Cells process external and internal biochemical signals by means of signaling cascades, which constitute complex, dynamical networks. In this project we use novel deep (machine) learning techniques to decompose such networks in their building blocks in order to elucidate the overall structure. Read more 

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Tue Jun 27 05:23:42 CEST 2017
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