Computational morphodynamics leverages computer simulations to investigate how living organisms grow and develop over space and time. Building on data and observations from biological experiments, researchers create predictive models of growth and morphogenesis. These models not only help clarify the underlying mechanisms but also generate testable predictions that can confirm or challenge the models' validity through experimentation.

This collection explores the benefits as well as the challenges of this approach. These include the need for models that connect individual cell behavior with overall tissue development, and  the importance of understanding the feedback between growth mechanics and molecular or chemical signaling. In short, computational morphodynamics can provide powerful tools to study and formalize the rules behind the dynamic processes driving plant form and development.

Submissions are open.

Guest Editors:

• Henrik Jönsson (Sainsbury Laboratory Cambridge, UK)
• Renske Vroomans (Sainsbury Laboratory Cambridge, UK)
• Richard Smith (John Innes Centre, UK)
• Argyris Zardilis (Sainsbury Laboratory Cambridge, UK)