Structural causes of pattern formation and loss through model-independent bifurcation analysis

During development, precise cellular patterning is essential for the formation of functional tissues and organs. These patterns arise from conserved signaling networks that regulate communication both within and between cells. Here, we develop and present a model-independent ordinary differential equation (ODE) framework for analyzing pattern formation in a homogeneous cell array. In contrast to traditional approaches that focus on specific equations, our method relies solely on general assumptions about global intercellular communication (between cells) and qualitative properties of local intracellular biochemical signaling (within cells). Prior work has shown that global intercellular communication networks alone determine the possible emergent patterns in a generic system. We build on these results by demonstrating that additional constraints on the local intracellular signaling network lead to a single stable pattern which depends on the qualitative features of the network. Our framework enables the prediction of cell fate patterns with minimal modeling assumptions, and provides a powerful tool for inferring unknown interactions within signaling networks by analyzing tissue-level patterns.

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Publication Details

Journal
Journal of Mathematical Biology
Published
2025-10-27
DOI
https://doi.org/10.1007/s00285-025-02296-9
Primary Topic
Nonlinear Dynamics and Pattern Formation
Type
article
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article

Structural causes of pattern formation and loss through model-independent bifurcation analysis

Adriana T. Dawes, Laura O'Brien
Journal of Mathematical Biology
Nonlinear Dynamics and Pattern Formation
article

Structural causes of pattern formation and loss through model-independent bifurcation analysis

Adriana T. Dawes, Laura O'Brien
article en

Abstract

During development, precise cellular patterning is essential for the formation of functional tissues and organs. These patterns arise from conserved signaling networks that regulate communication both within and between cells. Here, we develop and present a model-independent ordinary differential equation (ODE) framework for analyzing pattern formation in a homogeneous cell array. In contrast to traditional approaches that focus on specific equations, our method relies solely on general assumptions about global intercellular communication (between cells) and qualitative properties of local intracellular biochemical signaling (within cells). Prior work has shown that global intercellular communication networks alone determine the possible emergent patterns in a generic system. We build on these results by demonstrating that additional constraints on the local intracellular signaling network lead to a single stable pattern which depends on the qualitative features of the network. Our framework enables the prediction of cell fate patterns with minimal modeling assumptions, and provides a powerful tool for inferring unknown interactions within signaling networks by analyzing tissue-level patterns.

Journal of Mathematical BiologyVol. 91(6)
The Ohio State University (US)
Openalex Percentile: Top 64%
Nonlinear Dynamics and Pattern Formation
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Structural causes of pattern formation and loss through model-independent bifurcation analysis — Adriana T. Dawes, Laura O'Brien · Journal of Mathematical Biology (2025) | TGRS Research Map | TGRS