We are a research group at Heidelberg University and the European Bioinformatics Institute, part of the European Molecular Biology Laboratory (EMBL-EBI).

Our goal is to acquire a functional understanding of the deregulation of signalling networks in disease and to apply this knowledge to develop novel therapeutics. We focus on cancer, heart failure, auto-immune and fibrotic disease. Towards this goal, we integrate big "omics" data with mechanistic molecular knowledge into statistical and machine learning methods. To this end, we have developed a range of tools in different areas of biomedical research, mainly using the programming languages R and Python.

Legend:     Home page     R code     Python code     Package     Article       Docs

BioCypher A unifying framework for biomedical research knowledge graphs	CellNOpt Train logic models of signaling against omics data	CollecTRI Collection of Transcriptional Regulatory Interactions	CORNETO Unified framework for network inference problems
PYPI	BIOC		PYPI
COSMOS Mechanistic insights across multiple omics	Decoupler Infer biological activities from omics data using a collection of methods	DOT Optimization framework for transferring cell features from a reference data to spatial omics	GRETA Snakemake pipeline for benchmarking multimodal gene regulatory network inference methods
BIOC	PYPI     BIOC
LIANA+ Framework to infer inter- and intra-cellular signalling from single-cell and spatial omics	MetaProViz Metabolomics functional analysis and visualization	MISTy Explainable machine learning models for single-cell, highly multiplexed, spatially resolved data	NetworkCommons Context specific networks from omics data and prior-knowledge
		BIOC	PYPI
ocEAn Metabolic enzyme enrichment analysis	OmniPath Networks, pathways, gene annotations from 180+ databases	ParTIpy Archetypal analysis to identify functional trade-offs in biological data	PROGENy Activities of canonical pathways from transcriptomics data
	BIOC       PYPI       PYPI     CYTO	PYPI	BIOC

• BioChatter - A platform for the biomedical application of Large Language Models
• BioServices - Python package to access Bioinformatics Web Services
• Birewire - R package for the randomisation of bipartite graphs
• CARNIVAL - Causal reasoning to explore mechanisms in molecular networks
• DREAMTools - Code used in the scoring of DREAM challenges
• DoRothEA - Transcription factor activity inference
• DrugVsDisease - R/Cytoscape pipeline to compare drug and disease gene expression profiles
• GDSCTools - Python library dedicated to the study of pharmacogenomic relationships
• Kasumi - Identification of spatially localized neighborhoods of intra- and intercellular relationships from spatial omics
• MEIGO - Global optimization toolbox including metaheuristic and Bayesian methods
• MetalinksDB - Database of protein-metabolite and small molecule ligand-receptor interactions
• PHONEMeS - Logic modeling of phosphoproteomics
• SLAPenrich - R package to identify pathway-level enrichments of genetic alterations
• ScAPE - Single-cell Analysis of Perturbational Effects
• lipyd - Python module for lipidomics LC MS/MS data analysis