Maximilian Billmann

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Maximilian Billmann

We explore how genes interact in networks to regulate cells. We are particularly interested to learn how such functional interactions respond to environmental changes and how this functional capacity is impacted by disease-associated genetic variants. To this end, we develop computational methods to infer mechanistic cues from of large-scale perturbation data such as the Cancer Dependency Map (DepMap), single-cell-based CRISPR experiments, the currently ongoing human Genetic Interaction Network (GIN) or tissue type-resolved expression atlases. Our methods aim at understanding and utilizing different types of perturbation data, improving data reproducibility and guide experimental efforts to maximize the information gain towards a DepMap that covers genetic, environmental and phenotypic complexity of a cancer cell.

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