Landscape and Flux Theory for Nonequilibrium Biological Systems

Abstract: Life is characterized by a myriad of complex dynamic processes allowing organisms to grow, reproduce, and evolve. Physical approaches for describing systems out of thermodynamic equilibrium have been increasingly applied to living systems, which often exhibit phenomena not found in those traditionally studied in physics. Spectacular advances in experimentation during the last decade or two, for example, in microscopy, single-cell dynamics, in the reconstruction of subcellular and multicellular systems outside of living organisms, and in high throughput data acquisition, have yielded an unprecedented wealth of data on cell dynamics, genetic regulation, and organismal development. These data have motivated the development of concepts and tools to dissect the physical mechanisms underlying biological processes. Notably, landscape and flux theory has been proven useful in this endeavor [1,2]. Together with concepts and tools developed in other areas of nonequilibrium physics, significant progress has been made in unraveling the principles underlying cellular regulatory networks, differentiation and development, cancer, neural network dynamics, population dynamics, ecology, and evolution. Here, recent advances are reviewed with examples such as cell fate decision making with low and high throughput experimental data [3,4]. Many of these results are expected to be important as the field continues to build our understanding of life. 

References 
[1] Xiaona Fang, Karsten Kruse, Ting Lu, Jin Wang*. Nonequilibrium physics in biology. Rev. Mod.  
Phys. 91, 045004 (2019). 

[2] Jin Wang*,  Landscape and flux theory of non-equilibrium dynamical systems with application to 
biology, Advances in Physics, 64:1, 1-137. (2015).

[3] Ligang Zhu, Jin Wang*, Quantifying Landscape-Flux via Single-Cell Transcriptomics Uncovers the 
Underlying Mechanism of Cell Cycle. Adv. Sci. 2308879 (2024) 

[4] Ligang Zhu, Songlin Yang, Kun Zhang, Hong Wang, Xiaona Fang*, and Jin Wang*. Uncovering underlying physical 
principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics. Proc. Natl. Acad. 
Sci. USA 121 :34, e2401540121 (2024)