Selected Publication


scGen predicts single-cell perturbation responses

Predicting cellular behavior in silico: Trained on data that capture stimulation effects for a set of cell types, scGen can be used to model cellular responses in a new cell type. © Helmholtz Zentrum München

scGen is a tool that promises to reshape the way we study disease and disease treatment on a cellular level. Mohammad Lotfollahi, Alex Wolf and Fabian Theis at the Institute of Computational Biology developed scGen, an AI-powered tool for predicting a cell’s behavior in silico. scGen will help map and study cellular response to disease and treatment beyond experimentally available data.

For more information read the press release of the Helmholtz Zentrum München or click here for the original publication