The Computational Cell Fate Lab develops computational models to understand how cells communicate, process information, and make decisions about cell fate.
In the contemporary scientific landscape, novel computational tools are key to extract deeper insight from increasingly complex experimental datasets. In the Computational cell fate group, we address this challenge by integrating mechanistic modeling from biophysics and mathematics with data-driven, deep learning approaches. These models are trained and applied to single cell multi-Omics data to investigate fundamental questions about cell behavior including:
1) How do cells convert noisy signals from their surrounding environment in the form of cell-cell communication into robust decisions about cell fate determination?
2) How is information relayed across temporal and spatial scales from genes to cells and to tissues through multilayered regulatory networks?
These computational models are often developed as bioinformatics packages for the analysis of various types of high throughput data, such as single cell RNA sequencing.
We are located in the Radboud Institute for Molecular Life Sciences (RIMLS) at Radboud University, and collaborate with other group within RIMLS and internationally to validate and apply these predictions to multiple biological contexts such as development and cancer progression.
September 2026: Santhosh (PhD student), Michiel (Master student),
and Lisanne (Master student) join the group!
September 2026: Federico joins the
Radboud Young Academy”.
August 2026: The paper
“Robust identification of cell-cell communication
heterogeneity in single cells” is out in Cell systems.