Error Threshold of Fully Random Eigen Model

Species evolution is essentially a random process of interaction between biological populations and their environ- ments. As a result, some physical parameters in evolution models are subject to statistical fluctuations. In this work, two important parameters in the Eigen model, the fitness and muta...

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Bibliographic Details
Published inChinese physics letters Vol. 32; no. 1; pp. 170 - 173
Main Authors Li, Duo-Fang, Cao, Tian-Guang, Geng, Jin-Peng, Qiao, Li-Hua, Gu, Jian-Zhong, Zhan, Yong
Format Journal Article
LanguageEnglish
Published 2015
Subjects
Computer simulation
Crossovers
Errors
Fluctuation
Mathematical models
Mutations
Randomization
Thresholds
本征
物理参数
物种进化
生物种群
相互作用
误差阈值
随机模型
随机过程
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ISSN0256-307X
1741-3540
DOI10.1088/0256-307X/32/1/018702

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Summary:Species evolution is essentially a random process of interaction between biological populations and their environ- ments. As a result, some physical parameters in evolution models are subject to statistical fluctuations. In this work, two important parameters in the Eigen model, the fitness and mutation rate, are treated as Gaassian dis- tributed random variables simultaneously to examine the property of the error threshold. Numerical simulation results show that the error threshold in the fully random model appears as a crossover region instead of a phase transition point, and ＆s the fluctuation strength increases the crossover region becomes smoother and smoother. Furthermore, it is shown that the randomization of the mutation rate plays a dominant role in changing the error threshold in the fully random model, which is consistent with the existing experimental data. The implication of the threshold change due to the randomization for antiviral strategies is discussed.
Bibliography:11-1959/O4
Species evolution is essentially a random process of interaction between biological populations and their environ- ments. As a result, some physical parameters in evolution models are subject to statistical fluctuations. In this work, two important parameters in the Eigen model, the fitness and mutation rate, are treated as Gaassian dis- tributed random variables simultaneously to examine the property of the error threshold. Numerical simulation results show that the error threshold in the fully random model appears as a crossover region instead of a phase transition point, and ＆s the fluctuation strength increases the crossover region becomes smoother and smoother. Furthermore, it is shown that the randomization of the mutation rate plays a dominant role in changing the error threshold in the fully random model, which is consistent with the existing experimental data. The implication of the threshold change due to the randomization for antiviral strategies is discussed.
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ISSN:0256-307X
1741-3540
DOI:10.1088/0256-307X/32/1/018702