Software

Python package to infer transition gene regulatory networks and key transcription factors involved in cell state transitions from scRNA-seq data.

Python package with Numba and OpenMP-powered C++ backends for fast and memory-efficient statistical testing in the presence of missing data.

R tool to infer differential kinase-substrate links from phosphoproteomics data.

Python package that facilitates leakage-reduced data splitting to enable realistic evaluation of ML models that are intended to be used in out-of-distribution scenarios.

Python tool to infer gene dysregulation events for individual samples in comparison to a control condition from gene expression data.

Python tool to quantify tissue heterogeneity based on spatial omics data.

Web tool for interactive exploration of putative epistatic interactions in eight complex diseases (late-onset Alzheimer's disease, bipolar disorder, coronary artery disease, hypertension, type-1 diabetes, type-2 diabetes, rheumatoid arthritis, inflammatory bowel disease).

Command line tool for network-based epistasis detection in complex diseases.

Plugin to turn your tool that outputs a list of genes or proteins into a feature rich, drug repurposing web tool with interactive network visualization.

BoostDiff is a Python tool to infer differential gene regulatory networks from gene expression data.