Literature DB >> 30441929

Discrete flux and velocity fields of probability and their global maps in reaction systems.

Anna Terebus1, Chun Liu2, Jie Liang1.   

Abstract

Stochasticity plays important roles in reaction systems. Vector fields of probability flux and velocity characterize time-varying and steady-state properties of these systems, including high probability paths, barriers, checkpoints among different stable regions, as well as mechanisms of dynamic switching among them. However, conventional fluxes on continuous space are ill-defined and are problematic when at the boundaries of the state space or when copy numbers are small. By re-defining the derivative and divergence operators based on the discrete nature of reactions, we introduce new formulations of discrete fluxes. Our flux model fully accounts for the discreetness of both the state space and the jump processes of reactions. The reactional discrete flux satisfies the continuity equation and describes the behavior of the system evolving along directions of reactions. The species discrete flux directly describes the dynamic behavior in the state space of the reactants such as the transfer of probability mass. With the relationship between these two fluxes specified, we show how to construct time-evolving and steady-state global flow-maps of probability flux and velocity in the directions of every species at every microstate and how they are related to the outflow and inflow of probability fluxes when tracing out reaction trajectories. We also describe how to impose proper conditions enabling exact quantification of flux and velocity in the boundary regions, without the difficulty of enforcing artificial reflecting conditions. We illustrate the computation of probability flux and velocity using three model systems, namely, the birth-death process, the bistable Schlögl model, and the oscillating Schnakenberg model.

Entities:  

Year:  2018        PMID: 30441929     DOI: 10.1063/1.5050808

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  3 in total

1.  Discrete and continuous models of probability flux of switching dynamics: Uncovering stochastic oscillations in a toggle-switch system.

Authors:  Anna Terebus; Chun Liu; Jie Liang
Journal:  J Chem Phys       Date:  2019-11-14       Impact factor: 3.488

2.  Limit theorems for generalized density-dependent Markov chains and bursty stochastic gene regulatory networks.

Authors:  Xian Chen; Chen Jia
Journal:  J Math Biol       Date:  2019-11-21       Impact factor: 2.259

3.  Unifying deterministic and stochastic ecological dynamics via a landscape-flux approach.

Authors:  Li Xu; Denis Patterson; Ann Carla Staver; Simon Asher Levin; Jin Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2021-06-15       Impact factor: 11.205

  3 in total

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