Evolution, ageing and speciation: Monte Carlo simulations of biological systems

Oliveira, S. Moss de

doi:10.1590/s0103-97332004000600003

Cited by 3 publications

(1 citation statement)

References 31 publications

(28 reference statements)

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“…The model has been successfull in reproducing the senescence of the pacific salmon , and has been modified to account for the antagonistic pleiotropy mechanism (Sousa and de Oliveira, 2001;Cebrat and Stauffer, 2005) and spatial distributions on a lattice (Makowiec, 2000). Speciation in age structured populations has also been of interest, and in specific sympatric speciation (Sousa, 2000;LuzBurgoa et al, 2003) and parapatric speciation (Schwammle et al, 2006), in some cases including sexual reproduction, diploid and even triploid organisms (de Oliveira, 2004;Sousa et al, 2003).…”

Section: Computational Modelling For Biological Agingmentioning

confidence: 99%

Evolution of the rate of biological aging using a phenotype based computational model

Kittas

2010

Journal of Theoretical Biology

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.Evolution of the rate of biological aging using a phenotype based computational model Aristotelis KittasTo cite this version: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Evolution of the rate of biological aging using a phenotype based computational model Aristotelis KittasDepartment of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece AbstractIn this work I introduce a simple model to study how natural selection acts upon aging, which focuses on the viability of each individual. It is able to reproduce the Gompertz law of mortality and can make predictions about the relation between the level of mutation rates (beneficial/deleterious/neutral), age at reproductive maturity and the degree of biological aging. With no mutations, a population with low age at reproductive maturity R stabilizes at higher density values, while with mutations it reaches its maximum density, because even for large pre-reproductive periods each individual evolves to survive to maturity. Species with very short pre-reproductive periods can only tolerate a small number of detrimental mutations. The probabilities of detrimental (P d ) or beneficial (P b ) mutations are demonstrated to greatly affect the process. High absolute values produce peaks in the viability of the population over time. Mutations combined with low selection pressure move the system towards weaker phenotypes. For low values in the ratio P d /P b , the speed at which aging occurs is almost independent of R, while higher values favor significantly species with high R. The value of R is critical to whether the population survives or dies out. The aging rate is controlled by P d and P b and the amount the viability of each individual is modified, with neutral mutations allowing the system more "room" to evolve. The process of aging in this simple model is revealed to be fairly complex, yielding a rich variety of results.

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Section: Computational Modelling For Biological Agingmentioning

confidence: 99%

Evolution of the rate of biological aging using a phenotype based computational model

Kittas

2010

Journal of Theoretical Biology

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Simulation of the Evolution of Aging: Effects of Aggression and Kin-Recognition

Krivenko

Burtsev

Advances in Artificial Life

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Catastrophic senescence and semelparity in the Penna aging model

Piñol

Banzon

2010

Theory Biosci.

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The catastrophic senescence of the Pacific salmon is among the initial tests used to validate the Penna aging model. Based on the mutation accumulation theory, the sudden decrease in fitness following reproduction may be solely attributed to the semelparity of the species. In this work, we report other consequences of mutation accumulation. Contrary to earlier findings, such dramatic manifestation of aging depends not only on the choice of breeding strategy but also on the value of the reproduction age, R, and the mutation threshold, T. Senescence is catastrophic when T ≤ R. As the organism's tolerance for harmful genetic mutations increases, the aging process becomes more gradual. We observe senescence that is threshold dependent whenever T > R. That is, the sudden drop in survival rate occurs at age equal to the mutation threshold value.

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Evolution, ageing and speciation: Monte Carlo simulations of biological systems

Cited by 3 publications

References 31 publications

Evolution of the rate of biological aging using a phenotype based computational model

Evolution of the rate of biological aging using a phenotype based computational model

Simulation of the Evolution of Aging: Effects of Aggression and Kin-Recognition

Catastrophic senescence and semelparity in the Penna aging model

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