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首页> 外文期刊>International Journal of Modern Physics, C. Physics and Computers >Crossing time through the fitness barrier in an asymmetric multiplicative or additive landscape in the mutation-selection model
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Crossing time through the fitness barrier in an asymmetric multiplicative or additive landscape in the mutation-selection model

机译:突变选择模型中不对称乘积或加法情形下穿越健身障碍的时间

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摘要

This study examines the dependence of crossing time on sequence length for a finite population in an asymmetric multiplicative, or additive, landscape with a positive asymmetric parameter and a fixed extension parameter in three types of mutation-selection model: the coupled discrete-time model, the coupled continuous-time model, and the decoupled continuous-time model. The crossing times for a finite population in the three types of mutation-selection model began to deviate from the crossing times for an infinite population at a critical sequence length. It then increased exponentially as a function of sequence length in the stochastic region where the sequence length was much longer than the critical sequence length. The exponentially increasing rates of the crossing times in the three types of mutation-selection model were similar to each other. These rates were decreased by increasing the asymmetric parameter. Once the asymmetric parameter reached a certain limit the crossing times for the three models in the stochastic region could not be decreased further by increasing the asymmetric parameter past this limit.
机译:这项研究研究了三种类型的突变选择模型中具有正不对称参数和固定扩展参数的不对称乘积或加法景观中有限种群的穿越时间对序列长度的依赖性。耦合连续时间模型和解耦连续时间模型。在三种类型的突变选择模型中,有限种群的穿越时间开始偏离临界序列长度下无限种群的穿越时间。然后,它在随机区域中随序列长度呈指数增加,在随机区域中,序列长度比临界序列长度长得多。在三种类型的突变选择模型中,穿越时间的指数增长速率彼此相似。这些速率通过增加不对称参数而降低。一旦不对称参数达到某个极限,就无法通过增加不对称参数超过此极限来进一步减少随机区域中三个模型的穿越时间。

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