TY - JOUR
T1 - A solution of the Crow-Kimura evolution model on fluctuating fitness landscape
AU - Suvorov, Vladimir
AU - Saakian, David B.
AU - Lynch, Michael
N1 - Funding Information:
DBS thanks for the support the SCS of Armenia, grants Nos. 20TTAT-QTa003 and 21T-1C037 and Faculty Research Funding Program 2022 implemented by the Enterprise Incubator Foundation with the support of PMI Science. ML thanks for the support National Institutes of Health, R35-GM122566-01, 2017-2022, National Science Foundation, DBI-2119963, 2021-2026, Moore and Simons Foundations, Grant 735927, 2020-2023.
Publisher Copyright:
Copyright © 2023 EPLA
PY - 2023/6
Y1 - 2023/6
N2 - The article discusses the Crow-Kimura model in the context of random transitions between different fitness landscapes. The duration of epochs, during which the fitness landscape is constant over time, is modeled by an exponential distribution. To obtain an exact solution, a system of functional equations is required. However, to approximate the model, we consider the cases of slow or fast transitions and calculate the first-order corrections using either the transition rate or its inverse. Specifically, we focus on the case of slow transitions and find that the average fitness is equal to the average fitness for evolution on static fitness landscapes, but with the addition of a load term. We also investigate the model for a small number of genes and identify the exact transition points to the transient phase.
AB - The article discusses the Crow-Kimura model in the context of random transitions between different fitness landscapes. The duration of epochs, during which the fitness landscape is constant over time, is modeled by an exponential distribution. To obtain an exact solution, a system of functional equations is required. However, to approximate the model, we consider the cases of slow or fast transitions and calculate the first-order corrections using either the transition rate or its inverse. Specifically, we focus on the case of slow transitions and find that the average fitness is equal to the average fitness for evolution on static fitness landscapes, but with the addition of a load term. We also investigate the model for a small number of genes and identify the exact transition points to the transient phase.
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U2 - 10.1209/0295-5075/acd65b
DO - 10.1209/0295-5075/acd65b
M3 - Article
AN - SCOPUS:85161294424
SN - 0295-5075
VL - 142
JO - EPL
JF - EPL
IS - 5
M1 - 57003
ER -