On this page
Virtually all biological processes rely on the careful orchestration of a multitude of components, from molecules to cells, organs and entire organisms. Networks provide a powerful framework for describing and understanding these complex systems. Our group is specialized in network theory and its application in biology and medicine. A particular focus of our work are the molecular networks that form the mechanistic basis of all biological processes. We try to understand how these networks are organized and how they are perturbed in diseases. We work closely with experimental biologists, as well as clinical researchers to tackle both fundamental and practical challenges, ranging from deciphering the cellular arithmetic of perturbations to identifying mutations that cause genetic diseases.
Networks are not only our primary research objects, but also serve as a common language for our extremely diverse team. Our backgrounds include biology, computer science, physics and mathematics, but also architecture and arts. This diversity is also reflected in the wide range of methodologies that we develop and apply. With network expertise as common denominator, we also routinely use bioinformatics methods, machine learning techniques, advanced mathematical concepts, and Virtual Reality technology for exploring big biological datasets. Our research is often a collaborative effort with local and international partners, who provide us with exciting data and deep expertise on specific biological topics.
Jörg Menche studied physics in Germany and Brazil. During his PhD at the Max Planck Institute of Colloids and Interfaces he specialized in network theory. He did a postdoc in Boston at Northeastern University and Dana Farber Cancer Institute. He moved to Vienna in 2015 to start his own group at the CeMM Research Center for Molecular Medicine. Since 2020, he holds a joint professorship at the Max Perutz Labs and the Faculty of Mathematics of the University of Vienna.
We developed a novel mathematical framework that provides a deeper understanding of how drugs interact with each other. The framework offers the first rigorous approach to quantifying how perturbations with high-dimensional effects influence each other. Our analysis of over 30k drug pairs applied to cell lines identified almost 2000 interactions and sheds new light on how drugs perturb the molecular network within the cell.
[(2019) Caldera et al., Nature Communications. DOI: 10.1038/s41467-019-13058-9]
Virtual Reality (VR) technology opens up completely new ways of interacting with large, complex data in an intuitive and immersive fashion. We are developing a VR platform for exploring genome-scale molecular networks and identifying genetic mutations that cause rare hereditary diseases. Our platform represents the first application of this technology for state-of-the-art biomedical data analysis.
Our work laid out the theoretical basis for how molecular networks can be understood as maps to study molecular disease mechanisms. The methodology can be applied to address numerous questions at the forefront of network medicine, from elucidating the molecular origins of relationships between diseases, to interpreting genome-wide association study data or identifying promising drug targets.
[(2015) Menche et al., Science. DOI: 10.1126/science.1257601]
2016-2024; Topic: Network Medicine — An interactome-based approach to rare diseases
2017-2020; Topic: Systems precision medicine of inborn errors of the immune system
2019-2024; Topic: Network-approaches to diseases associated with early development
2019-2020; Topic: Virtual Reality (VR) data analysis platform
2020; Topic: Virtual Reality (VR) platform development