Modeling yeast population dynamics in space environments using agent-based modeling and genetic algorithm
Abstract
We demonstrate how computational simulations of yeast (Saccharomyces cerevisiae) colony growth using a hybrid model that combines cellular automata and genetic algorithms can provide insights into the potential effects of initial radiation resistance and radiation-induced genetic mutations. Our preliminary results suggest that initial radiation resistance is a critical determinant of population survival, whereas increasing the probability of radiation-induced mutations appears to have limited impact on yeast growth. While these results are based on a limited number of simulations, they offer initial insights that can guide future, more comprehensive investigations on the complex role of radiation on yeast populations.
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