scholarly journals On Diffusive Stability of Eigen’s Quasispecies Model

2014 ◽  
Vol 22 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Alexander S. Bratus ◽  
Chin-Kun Hu ◽  
Mikhail V. Safro ◽  
Artem S. Novozhilov
Keyword(s):  
Quasispecies Model ◽  
Eigen’S Quasispecies Model

scholarly journals Population genetics approach to the quasispecies model

1996 ◽  
Vol 54 (4) ◽  
pp. 4048-4053 ◽  
Author(s):  
D. Alves ◽  
J. F. Fontanari
Keyword(s):  
Population Genetics ◽  
Quasispecies Model

Error Thresholds in Genetic Algorithms

2006 ◽  
Vol 14 (2) ◽  
pp. 157-182 ◽  
Author(s):  
Gabriela Ochoa
Keyword(s):  
Genetic Algorithms ◽  
Selection Pressure ◽  
Evolutionary Process ◽  
Critical Value ◽  
Mutation Rates ◽  
Genomic Information ◽  
Quasispecies Model ◽  
Error Catastrophe ◽  
Important Notion ◽  
Quasispecies Evolution

The error threshold of replication is an important notion in the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an evolutionary process are destroyed more frequently than selection can reproduce them. With mutation rates above this critical value, an error catastrophe occurs and the genomic information is irretrievably lost. Therefore, studying the factors that alter this magnitude has important implications in the study of evolution. Here we use a genetic algorithm, instead of the quasispecies model, as the underlying model of evolution, and explore whether the phenomenon of error thresholds is found on finite populations of bit strings evolving on complex landscapes. Our empirical results verify the occurrence of error thresholds in genetic algorithms. In this way, this notion is brought from molecular evolution to evolutionary computation. We also study the effect of modifying the most prominent evolutionary parameters on the magnitude of this critical value, and found that error thresholds depend mainly on the selection pressure and genotype length.

A SIMPLE EVOLUTIONARY MODEL FOR CANCER CELL POPULATION AND ITS IMPLICATIONS ON CANCER THERAPY

2009 ◽  
Vol 23 (25) ◽  
pp. 2999-3011 ◽  
Author(s):  
PENG YAO ◽  
SHUTANG WEN ◽  
BAOSHUN LI ◽  
YUXIAO LI
Keyword(s):  
Cancer Therapy ◽  
Cancer Cell ◽  
Cell Population ◽  
Fitness Landscape ◽  
Evolutionary Model ◽  
Evolutionary Games ◽  
Cellular Interactions ◽  
Malignant Cells ◽  
Quasispecies Model ◽  
Cancer Cell Population

We established a simple evolutionary model based on the cancer stem cell hypothesis. By taking cellular interactions into consideration, we introduced the evolutionary games theory into the quasispecies model. The fitness values are determined by both genotypes and cellular interactions. In the evolutionary model, a cancer cell population can evolve in different patterns. For single peak intrinsic fitness landscape, the evolution pattern can transit with increasing differentiation probability from malignant cells to benign cells in four different modes. For a large enough value of differentiation probability, the evolution is always the case that the malignant cells extinct ultimately, which might give some implications on cancer therapy.

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