News

In our paper "Lacking mechanistic disease definitions hamper progress in network medicine and beyond", we show that it can be problematic to uncritically use large-scale disease association databases for pathomechanism mining.

In this three-year project, we will develop a network-based software platform for dynamic and explorative analysis of of the CHRIS cohort data. The project will be carried out in collaboration with TUM, Eurac Research, and UNIBZ.

Together with partners from TUM and University of Hamburg, we will develop dimensionality reduction techniques for scRNA-seq data based on inference of differential gene regulatory network. The new methods will be used to investigate CD4 helper T cell exhaustion, a limiting factor in immunotherapy.

We are happy to announce that our paper "Querying Temporal Anomalies in Healthcare Information Systems and Beyond" has been accepted at ADBIS 2022.