New applications of an old individual-based model for biological dynamics.
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2023
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A simplified representation or interpretation of reality using conceptual and mathematical models plays a role in
understanding important phenomena, especially biological ones. Based on Medawar’s mutation accumulation
theory, which predicts that the strength of natural selection decreases with age, favouring the accumulation of
deleterious genes to be expressed at advanced ages, an individual-based model (IBM) published in 1995 was
designed to demonstrate the biological ageing mechanism, with each individual being represented by a bitstring
in a chronological manner. This model is called Penna Model (Penna, 1995) in honour of the creator, the
physicist Thadeu Josino Pereira Penna. For this first time, this article carries out a systematic review of the use of
Penna Model to assess its applicability in other phenomena and biological mechanisms. Our results indicate that
the model was extensively explored and improved by researchers from different parts of the world, through small
changes in the structure and base parameters of the model aimed at the biological phenomena of interest
including Ecology, Evolutionary Ecology and Genetics issues. These changes have allowed the use of the model in
other biological phenomena besides aging, with studies in systems of predation, competition, fragmentation,
natural selection, speciation, genetics, immunology, epidemiology and others. The model is highlighted as a
fairly flexible tool for applied biological dynamics of simple use, with the possibility of implementing different
scales - temporal or spatial; and different languages - computational, logical or numerical; in addition to the
possibility of inserting parameters that modify the individual and/or population that allow consistent results for
decision-making.
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Bitstring, Mutation accumulation, Penna model
Citação
FERREIRA, F. K. et al. New applications of an old individual-based model for biological dynamics. Ecological Modelling, v. 476, artigo 110234, fev. 2023. Disponível em: <https://www.sciencedirect.com/science/article/pii/S0304380022003325>. Acesso em: 06 jul. 2023.