Laboratory of Computational Systems Biology

Cells acquire, maintain and change their identities through coordinated molecular programs spanning signalling, transcriptional, epigenomic and post-transcriptional regulation. Understanding these programs is central to explaining development, stem-cell differentiation, organoid formation and disease.

Our laboratory develops statistical and machine-learning methods to reconstruct and interpret these regulatory programs from single-cell, spatial and multimodal omics data. By integrating computational modelling with stem-cell, organoid and disease biology, we aim to understand how cell identity is established, how cell-fate decisions are controlled, and how disrupted cell states can be linked to therapeutic opportunities.

Our research aims to:

• Develop interpretable AI and statistical methods for single-cell, spatial and multimodal omics.
• Reconstruct regulatory programs that control cell identity and cell-fate decisions.
• Model cell-state transitions during differentiation, organoid development and disease.
• Establish robust computational tools and benchmarks for the research community.
• Translate cell-state models into strategies for stem-cell engineering, disease modelling and therapeutic prioritisation.