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A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces
Published on: March 1, 2017
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Towards a mathematical framework for modelling cell fate dynamics
Sean T Vittadello1,2,3, Léo Diaz1,2, Yujing Liu1
1School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia.
Journal of Mathematical Biology
|September 24, 2025
Summary
This study introduces random dynamical systems as a new framework for modeling cell fate during development. This approach offers a more flexible and assumption-free alternative to existing models like Waddington's epigenetic landscape.
Area of Science:
- Developmental Biology
- Mathematical Biology
- Computational Biology
Background:
- Cellular development involves complex interactions between cells and their environment.
- Existing models of cell fate, such as Waddington's epigenetic landscape, offer simplifications but may overlook environmental influences.
- There is a lack of consistent definitions for fundamental concepts like 'cell type' and 'cell state' in developmental biology literature.
Purpose of the Study:
- To critically evaluate existing theoretical and mathematical models of cell fate.
- To introduce and explore random dynamical systems as a novel framework for modeling cell development.
- To provide a more flexible and assumption-free approach to understanding cell fate dynamics.
Main Methods:
- Review and critique of existing cell fate modeling approaches (trees, networks, landscapes).
- Introduction of random dynamical systems as a conceptual and mathematical framework.
- Development of basic concepts within the random dynamical systems framework.
Main Results:
- Existing models often oversimplify complex developmental processes.
- Random dynamical systems offer a flexible framework for modeling cell fate.
- This new approach can be discussed in relation to classical models like Waddington's landscape.
Conclusions:
- A more comprehensive approach to modeling cell fate is needed, explicitly including environmental influences.
- Random dynamical systems provide a promising alternative for future research in developmental biology.
- This framework allows for a more nuanced understanding of cell fate determination and differentiation.
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