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Driving directed differentiation: Bridging microscopic biological processes and macroscopic Hill function modeling

  • Yuchen Miao
  • , Lin Du
  • , Shutong Liu
  • , Zichen Deng* (Corresponding Author)
  • , Celso Grebogi
  • *Corresponding author for this work
  • MIIT Key Laboratory of Dynamics and Control of Complex System
  • Northwestern Polytechnical University Xian
  • Shaanxi Normal University

Research output: Contribution to journalArticlepeer-review

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Abstract

Cell differentiation emerges as an irreversible biological transition governed by the expression of core gene circuit. While Hill functions provide phenomenological descriptions of gene network behaviors, when addressing the issue of cell differentiation, it is often inevitable to introduce a time-correlated driving term, which undermines the theoretical closure. Utilizing a prototypical gene circuit, we develop a microscopic theory for the Hill functions based on the detailed biochemical reactions and the principles of statistical physics. This approach establishes equivalence mappings between different biological scales: the complete microscopic reaction network model, reduced microscopic model, and effective mesoscopic model. Under this equivalence, without introducing external information, we identify the differentiation-driving forces, while the remaining components of the model are exactly represented by Hill functions. Our theoretical results also demonstrate that the macroscopic force described by Hill functions maintains cellular stability over small time scales, whereas intrinsic driving forces propel directed differentiation of cells across large time scales. Furthermore, numerical simulations conducted using equivalent methods agrees with our theoretical findings. The derived relationships between reaction kinetic constants and phenomenological parameters establish a physical basis for bridging genotype-phenotype mapping in developmental systems.
Original languageEnglish
Article number131774
Number of pages12
JournalPhysica. A, Statistical Mechanics and its Applications
Volume698
Early online date6 Jul 2026
DOIs
Publication statusE-pub ahead of print - 6 Jul 2026

Data Availability Statement

Data will be made available on request.

Funding

This work was supported by the National Key Research and Development Program of China (No. 2025YFA1016800) and National Natural Science Foundation of China (NNSFC, Grant No. 12472357, 12402034). We also gratefully acknowledge the support received from Shaanxi Province Outstanding Youth Fund Project (No. 2024JC-JCQN-05) and the 111 Project (No. BP0719007).

FundersFunder number
National Key Research and Development Program of China2025YFA1016800
National Natural Science Foundation of China12472357, 12402034
Shaanxi Province Outstanding Youth Fund Project 2024JC-JCQN-05
111 ProjectBP0719007

    Keywords

    • cell differentiation dynamics
    • hill functions
    • Waddington landscape
    • multiscale modelling
    • gene regulatory networks

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