Software

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

DIGEST is a systems medicine tool for the in silico validation of gene and disease sets, clusterings, and subnetworks w.r.t. genetic and functional coherence. It is available as a web service, as a Python package, and via a REST API.

ROBUST is a Python tool which uses enumeration of diverse prize-collecting Steiner trees to compute disease modules that are robust to random bias.

Fever-PCA (federated principal component analysis for vertically partitioned data) is a federated, privacy-preserving tool for principal component analysis, including patient stratification and dimensionality reduction.

Flimma is a privacy-preserving hybrid federated tool for differential gene expression analysis. Flimma by design preserves the privacy of the local data, since the expression profiles never leave the local execution sites and shared meta-parameters are protected via secure multi-party computation.

NeDRex (network-based drug repurposing and exploration) is an interactive network medicine platform for disease module identification and drug repurposing.

The AIMe registry for artificial intelligence in biomedical research is a community-driven platform for reporting biomedical AI systems. It allows authors of new biomedical AIs to report their models in an explicit and transparent fashion and thereby fosters comparability and reproducibility.

BiCoN allows to stratify patients while elucidating disease mechanisms. BiCoN is a network-constrained biclustering approach, which restricts biclusters to functionally related genes connected in molecular networks and maximizes the expression difference between two groups of patients.

CoVex is a unique online network and systems medicine platform for data analysis that integrates virus-human interactions for SARS-CoV-2 and SARS-CoV-1. It implements different network-based approaches for the identification of new drug targets and new repurposable drugs.