BIONETS lab goes digital history: In our paper "On the role of network topology in German-Jewish recommendation letter networks", we analyze the role of professional networks for emigration of German-Jewish academics from Nazi Germany.
TF-Prioritizer is an automated pipeline that prioritizes condition-specific transcription factors from multimodal data and generates an interactive web report. It accepts ATAC, DNase, or ChIP sequencing and RNA sequencing data as input and identifies TFs with differential activity
Our paper "TF-Prioritizer: a Java pipeline to prioritize condition-specific transcription factors" has just appeared in GigaScience. TF-Prioritizer accepts ATAC, DNase, or ChIP sequencing and RNA sequencing data as input and identifies transcription factors with differential activity.
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.
We are happy to announce that our paper "The edge-preservation similarity for comparing rooted, unordered, node-labeled trees" has just appeared in Pattern Recognition Letters.
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.
