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MorphoGrad: A MATLAB toolbox for simulating steady-state morphogen gradients under cell-to-cell variability
Jan A Adelmann1, Roman Vetter1, Dagmar Iber1
1Department of Biosystems Science and Engineering, ETH Zürich, Schanzenstrasse 44, 4056 Basel, Switzerland; Swiss Institute of Bioinformatics, Schanzenstrasse 44, 4056 Basel, Switzerland.
STAR Protocols
|June 4, 2026
Summary
This study introduces a MATLAB protocol for simulating morphogen gradients in tissues, incorporating cell-to-cell variability. The method enhances in silico modeling of biological patterning precision.
Area of Science:
- Developmental biology
- Computational biology
- Systems biology
Background:
- Accurately modeling morphogen gradients in silico is crucial for understanding tissue patterning.
- Biological variability at the cellular level presents a significant challenge for computational models.
Purpose of the Study:
- To present a MATLAB-based protocol for simulating steady-state morphogen gradients in 1D and 2D tissues.
- To incorporate and analyze cell-to-cell variability in model parameters within these simulations.
Main Methods:
- Development of a MATLAB protocol detailing steps for simulation setup.
- Configuration of cell-based geometries and reaction-diffusion equations.
- Implementation of stochastic parameter variability and analysis of resulting gradients.
Main Results:
- Successful simulation of steady-state morphogen gradients in silico.
- Quantification of patterning precision under conditions of stochastic parameter variability.
- Demonstration of the protocol's applicability to both one- and two-dimensional tissue models.
Conclusions:
- The developed protocol provides a robust framework for in silico study of morphogen gradient dynamics.
- Accounting for cell-to-cell variability is essential for realistic simulations of tissue patterning.
- This tool aids in dissecting the contribution of parameter stochasticity to developmental robustness.
