Boreskov

OP‐29mutations and/or inbreeding. Thereby the modeling of both polymery and pleiotropy ispossible.An individual’s phenotype is modeled as a list of traits, which are also described withseveral various implementations. Traits can be either quantitative or qualitative. Anindividual is described, in addition, by parameters like age and state (presence of substratesand regulators). Those parameters in combination with phenotype affect the fitness of anindividual. While describing fitness, we distinguish the fitness with respect to population(number of offsprings) and survival of an individual. The first is defined as a result of aninteraction individual‐population, while the second – individual‐environment.Environment has fixed dimensions and spatial location. It contains individuals of apopulation (or several populations), substrates and non‐substrate regulators. In this casesubstrates are exhaustible; their presence in environment depends upon organisms’ living.At the same time non‐substrate regulators are exhaustless in the sense that their presencedoes not affected by individuals, instead of this they depend on another external factors.In order to describe the mutual influence of various levels of organization we use specialsubmodels – “strategies” which describe the laws of layers changing. From a softwareengineering point of view, the layers contain data while strategies manipulate those data. Inthe present DEC version we consider the following strategies types: mutation andrecombination (refer to genotype layer); “genotype to phenotype” (binds correspondinglayers); “phenotype to fitness” (determines fitness and survival of an individual with regardto its phenotype, population and environmental conditions); reproduction strategy(determines the law of population size change taking into account environmental limitation,suggested growth model and another factors); migration strategy (determines the law ofindividuals movement).The DEC software package is implemented using C++. It has been adapted for use on MPIclusters. The method is still being verified on the classic problems of population genetics. Inparticular, it has been shown that Fisher’s fundamental theorem is satisfied in our models ofnatural selection for various population growth models. The population modeled contained100‐100 000 individuals, which had diploid genome of 10‐20 chromosomes; chromosomecontained 5‐10 loci; locus contained 1‐3 genes; individual had 1‐10 traits.[1]. S.A. Lashin, V.V. Suslov and Yu.G. Matushkin. Comparative Modeling Of Coevolution In Communities OfUnicellular Organisms: Adaptability And Biodiversity. Journal of Bioinformatics and ComputationalBiology,Vol. 8, No. 3 (2010) 627–643.80