An In Silico Model to Simulate the Evolution of Biological Aging

New models for evolutionary processes of mutation accumulation allow hypotheses about the age-specificity of mutational effects to be translated into predictions of heterogeneous population hazard functions. We apply these models to questions in the biodemography of longevity, including proposed explanations of Gompertz hazards and mortality plateaus, and use them to explore the possibility of melding evolutionary and functional models of aging.

We generalize the standard Penna bit-string model of biological ageing by assuming that each deleterious mutation diminishes the survival probability in every time interval by a small percentage. This effect is added to the usual lethal but age-dependent effect of the same mutation. We then find strong advantages or disadvantages of sexual reproduction (with males and females) compared to asexual cloning, depending on parameters.

The concept of random deaths in a computational model for population dynamics is critically examined. We claim that it is just an artifact, albeit useful, of computational models to limit the size of the populations and has no biological foundation. Alternative implementations of random deaths strategies are discussed and compared.

We present a simple model for biological aging. We studied it through computer simulations and we have found this model to reflect some features of real populations.

Based on the study of cellular aging using the single-cell model organism of budding yeast and corroborated by other studies, we propose the Emergent Aging Model (EAM). EAM hypothesizes that aging is an emergent property of complex biological systems, exemplified by biological networks such as gene networks. An emergent property refers to traits that a system has at the system level but which its low-level components do not. EAM is based on a quantitative definition of aging ...

Evolution is faced with a formidable challenge: refining the already highly optimised design of biological species, a feat accomplished through all preceding generations. In such a scenario, the impact of random changes (the method employed by evolution) is much more likely to be harmful than advantageous, potentially lowering the chances of reproduction of the affected individuals. The proposition of ageing as a nonadaptive phenomenon is robust and nearly universally acknowl...

A probability model is presented for the dynamics of mutation-selection balance in a haploid infinite-population infinite-sites setting sufficiently general to cover mutation-driven changes in full age-specific demographic schedules. The model accommodates epistatic as well as additive selective costs. Closed form characterizations are obtained for solutions in finite time, along with proofs of convergence to stationary distributions and a proof of the uniqueness of solutions...

We argue that the stochastic dynamics of interacting agents which replicate, mutate and die constitutes a non-equilibrium physical process akin to aging in complex materials. Specifically, our study uses extensive computer simulations of the Tangled Nature Model (TNM) of biological evolution to show that punctuated equilibria successively generated by the model's dynamics have increasing entropy and are separated by increasing entropic barriers. We further show that these sta...

Biological evolution continuously refines the design of species, resulting in highly optimised organisms over hundreds of millennia. Intuitively, we expect that random changes-evolution's primary mechanism-are more likely to be harmful than beneficial, leading to widespread detrimental effects in evolving species. The Evolvable Soma Theory of Ageing (ESTA) suggests that ageing is the cumulative result of these harmful effects, which predominantly cause bodily damage, while a ...

We use a simple model for biological ageing to study the mortality of the population, obtaining a good agreement with the Gompertz law. We also simulate the same model on a square lattice, considering different strategies of parental care. The results are in agreement with those obtained earlier with the more complicated Penna model for biological ageing. Finally, we present the sexual version of this simple model.