Towards a mathematical framework for modelling cell fate dynamics

An adult human body is made up of some 30 to 40 trillion cells, all of which stem from a single fertilized egg cell. The process by which the right cells appear to arrive in their right numbers at the right time at the right place - development - is only understood in the roughest of outlines. This process does not happen in isolation: the egg, the embryo, the developing foetus, and the adult organism all interact intricately with their changing environments. Conceptual and, increasingly, mathematical approaches to modelling development have centred around Waddington's concept of an epigenetic landscape. This perspective enables us to talk about the molecular and cellular factors that contribute to cells reaching their terminally differentiated state: their fate. The landscape metaphor is however only a simplification of the complex process of development; it for instance does not consider environmental influences, a context which we argue needs to be explicitly taken into account and from the outset. When delving into the literature, it also quickly becomes clear that there is a lack of consistency and agreement on even fundamental concepts; for example, the precise meaning of what we refer to when talking about a 'cell type' or 'cell state.' Here we engage with previous theoretical and mathematical approaches to modelling cell fate - focused on trees, networks, and landscape descriptions - and argue that they require a level of simplification that can be problematic. We introduce random dynamical systems as one natural alternative. These provide a flexible conceptual and mathematical framework that is free of extraneous assumptions. We develop some of the basic concepts and discuss them in relation to now 'classical' depictions of cell fate dynamics, in particular Waddington's landscape. This paper belongs to the special issue "Problems, Progress and Perspectives in Mathematical and Computational Biology".

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Publication Details

Journal
Journal of Mathematical Biology
Published
2025-09-24
DOI
https://doi.org/10.1007/s00285-025-02287-w
Primary Topic
Gene Regulatory Network Analysis
Type
article
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article

Towards a mathematical framework for modelling cell fate dynamics

Sean T. Vittadello, Yujing Liu, Léo Diaz, Michael P. H. Stumpf et al.
Journal of Mathematical Biology
Gene Regulatory Network Analysis
article

Towards a mathematical framework for modelling cell fate dynamics

Sean T. Vittadello, Yujing Liu, Léo Diaz, Michael P. H. Stumpf, Adriana Zanca
article en

Abstract

An adult human body is made up of some 30 to 40 trillion cells, all of which stem from a single fertilized egg cell. The process by which the right cells appear to arrive in their right numbers at the right time at the right place - development - is only understood in the roughest of outlines. This process does not happen in isolation: the egg, the embryo, the developing foetus, and the adult organism all interact intricately with their changing environments. Conceptual and, increasingly, mathematical approaches to modelling development have centred around Waddington's concept of an epigenetic landscape. This perspective enables us to talk about the molecular and cellular factors that contribute to cells reaching their terminally differentiated state: their fate. The landscape metaphor is however only a simplification of the complex process of development; it for instance does not consider environmental influences, a context which we argue needs to be explicitly taken into account and from the outset. When delving into the literature, it also quickly becomes clear that there is a lack of consistency and agreement on even fundamental concepts; for example, the precise meaning of what we refer to when talking about a 'cell type' or 'cell state.' Here we engage with previous theoretical and mathematical approaches to modelling cell fate - focused on trees, networks, and landscape descriptions - and argue that they require a level of simplification that can be problematic. We introduce random dynamical systems as one natural alternative. These provide a flexible conceptual and mathematical framework that is free of extraneous assumptions. We develop some of the basic concepts and discuss them in relation to now 'classical' depictions of cell fate dynamics, in particular Waddington's landscape. This paper belongs to the special issue "Problems, Progress and Perspectives in Mathematical and Computational Biology".

Journal of Mathematical BiologyVol. 91(5)
The University of Melbourne (AU), ARC Centre of Excellence for Mathematical and Statistical Frontiers (AU)
Openalex Percentile: Top 77%
Gene Regulatory Network Analysis
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