Author: David Blumenthal

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.

Funded projects: High-resolution protein-protein interaction networks for biomedical research

On July 1, Nicolai Meyerhöfer started as a doctoral researcher in the BIONETS lab. He will work on graph neural network models for prediction of tissue-specific protein-protein interactions.

In our joint retreat with the DaiSyBio group (TUM) in Peschiera del Garda, we had inspiring talks and discussions on hot topics and off topics in computational systems biology, ran two hackathons, and engaged in a series of team building events.

In our paper "Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases", we show how to flag and retrieve temporal inconsistencies in healthcare information systems.

In our paper "Drugst.One — a plug-and-play solution for online systems medicine and network-based drug repurposing", we present a versatile plugin to turn any tool that outputs a list of genes or proteins into a feature rich, drug repurposing web tool with interactive network visualization.

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.

Our Python test suite confinspect allows to assess the effect of demographic confounders such as sex and age on methods for inferring gene regulatory and gene co-expression networks.