Non-equilibrium statistical physics, transitory epigenetic landscapes, and cell fate decision dynamics

Area of Science:

• * Physics
• * Biology
• * Biophysics

Background:

• * Complex biological systems, including developmental and cell biology, exhibit robust behaviors from stochastic sub-cellular processes.
• * Statistical physics offers a framework to analyze these complex systems, connecting microscopic fluctuations to macroscopic observations.
• * Understanding cell-fate decisions is central to stem cell biology and developmental processes.

Purpose of the Study:

• * To connect different theoretical perspectives for qualitative insights into cell-fate decision-making.
• * To explore dynamical systems and statistical mechanics viewpoints on the Waddington or epigenetic landscape.
• * To highlight the necessity of non-equilibrium approaches for studying biological systems.

Main Methods:

• * Application of statistical physics principles to complex biological systems.
• * Analysis using dynamical systems theory.
• * Examination of the Waddington or epigenetic landscape from statistical mechanics perspectives.
• * Consideration of non-equilibrium thermodynamics and statistical mechanics.

Main Results:

• * Statistical physics provides a valuable lens for analyzing complex biological systems.
• * Cell-fate decisions in developmental biology arise from complex, stochastic sub-cellular processes.
• * Non-equilibrium approaches are essential for a comprehensive understanding of biological systems, which are inherently far from equilibrium.
• * Classical equilibrium models have limitations in explaining these dynamic biological processes.

Conclusions:

• * Integrating dynamical systems and statistical mechanics offers novel insights into cell-fate decisions.
• * Non-equilibrium statistical physics is indispensable for elucidating the dynamics of biological processes.
• * The study underscores the limitations of equilibrium-based models in capturing the far-from-equilibrium nature of life.