Monte Carlo Simulation of Age-Dependent Host-Parasite Relations

The possible coexistence of one host, one aggressive parasite and one non-lethal parasite is simulated using the Penna model of biological ageing. If the aggressive parasites survive the difficult initial times where they have to adjust genetically to the proper host age, all three species may survive, though the host number may be diminished by increasing parasite aggressivity.

The sexual version of the Penna model of biological ageing, simulated since 1996, is compared here with alternative forms of reproduction as well as with models not involving ageing. In particular we want to check how sexual forms of life could have evolved and won over earlier asexual forms hundreds of million years ago. This computer model is based on the mutation-accumulation theory of ageing, using bits-strings to represent the genome. Its population dynamics is studied b...

We describe the simulation method of modelling the population evolution using Monte Carlo based on the Penna model. Individuals in the populations are represented by their diploid genomes. Genes expressed after the minimum reproduction age are under a weaker selection pressure and accumulate more mutations than those expressed before the minimum reproduction age. The generated gradient of defective genes determines the ageing of individuals and age-structured populations are ...

We have simulated demographic changes in the human population using the Penna microscopic model, based on the simple Monte Carlo method. The results of simulations have shown that during a few generations changes in the genetic pool of a population are negligible, while improving the methods of compensation of genetic defects or genetically determined proneness to many disorders drastically affects the average life span of organisms. Age distribution and mortality of the simu...

The Penna model is a strategy to simulate the genetic dynamics of age-structured populations, in which the individuals genomes are represented by bit-strings. It provides a simple metaphor for the evolutionary process in terms of the mutation accumulation theory. In its original version, an individual dies due to inherited diseases when its current number of accumulated mutations, n, reaches a threshold value, T. Since the number of accumulated diseases increases with age, th...

We investigate the scaling properties of the Penna model, which has become a popular tool for the study of population dynamics and evolutionary problems in recent years. We find that the model generates a normalised age distribution for which a simple scaling rule is proposed, that is able to reproduce qualitative features for all genome sizes.

A stochastic genetic model for biological aging is introduced bridging the gap between the bit-string Penna model and the Pletcher-Neuhauser approach. The phenomenon of exponentially increasing mortality function at intermediate ages and its deceleration at advanced ages is reproduced for both the evolutionary steady-state population and the genetically homogeneous individuals.

Can unicellular organisms survive a drastic temperature change, and adapt to it after many generations? In simulations of the Penna model of biological ageing, both extinction and adaptation were found for asexual and sexual reproduction as well as for parasex. These model investigations are the basis for the design of evolution experiments with heterotrophic flagellates.

A large amount of population models use the concept of a carrying capacity. Simulated populations are bounded by invoking finite resources through a survival probability, commonly referred to as the Verhulst factor. The fact, however, that resources are not easily accounted for in actual biological systems makes the carrying capacity parameter ill-defined. Henceforth, we deem it essential to consider cases for which the parameter is unnecessary. This work demonstrates the pos...

We removed from the Penna model for biological ageing any random killing Verhulst factor. Deaths are due only to genetic diseases and the population size is fixed, instead of fluctuating around some constant value. We show that these modifications give qualitatively the same results obtained in an earlier paper, where the random killings (used to avoid an exponential increase of the population) were applied only to newborns.