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Exploring dissipative sources of non-Markovian biochemical reaction systems
被引:6
|作者:
Yang, Xiyan
[1
]
Chen, Yiren
[2
]
Zhou, Tianshou
[3
,4
]
Zhang, Jiajun
[3
,4
]
机构:
[1] Guangdong Univ Finance, Sch Financial Math & Stat, Guangzhou 510521, Peoples R China
[2] Shenzhen Univ, Coll Math & Stat, Shenzhen 518060, Peoples R China
[3] Sun Yat Sen Univ, Sch Math, Guangzhou 510275, Peoples R China
[4] Guangdong Prov Key Lab Computat Sci, Guangzhou 510275, Peoples R China
关键词:
GENE-EXPRESSION;
RANDOM-WALKS;
NOISE;
QUANTIFICATION;
ROBUSTNESS;
PROTEIN;
MODELS;
SPEED;
D O I:
10.1103/PhysRevE.103.052411
中图分类号:
O35 [流体力学];
O53 [等离子体物理学];
学科分类号:
070204 ;
080103 ;
080704 ;
摘要:
Many biological processes including important intracellular processes are governed by biochemical reaction networks. Usually, these reaction systems operate far from thermodynamic equilibrium, implying free-energy dissipation. On the other hand, single reaction events happen often in a memory manner, leading to non-Markovian kinetics. A question then arises: how do we calculate free-energy dissipation (defined as the entropy production rate) in this physically real case? We derive an analytical formula for calculating the energy consumption of a general reaction system with molecular memory characterized by nonexponential waiting-time distributions. It shows that this dissipation is composed of two parts: one from broken detailed balance of an equivalent Markovian system with the same topology and substrates, and the other from the direction-time dependence of waiting-time distributions. But, if the system is in a detailed balance and the waiting-time distribution is direction-time independent, there is no energy dissipation even in the non-Markovian case. These general results provide insights into the physical mechanisms underlying nonequilibrium processes. A continuous-time random-walk model and a generalized model of stochastic gene expression are chosen to clearly show dissipative sources and the relationship between energy dissipation and molecular memory.
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页数:17
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