46 research outputs found

    Analytical solution of a generalized Penna model

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    In 1995 T.J.Penna introduced a simple model of biological aging. A modified Penna model has been demonstrated to exhibit behaviour of real-life systems including catastrophic senescence in salmon and a mortality plateau at advanced ages. We present a general steady-state, analytic solution to the Penna model, able to deal with arbitrary birth and survivability functions. This solution is employed to solve standard variant Penna models studied by simulation. Different Verhulst factors regulating both the birth rate and external death rate are considered.Comment: 6 figure

    Forward-in-Time, Spatially Explicit Modeling Software to Simulate Genetic Lineages Under Selection

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    SELECTOR is a software package for studying the evolution of multiallelic genes under balancing or positive selection while simulating complex evolutionary scenarios that integrate demographic growth and migration in a spatially explicit population framework. Parameters can be varied both in space and time to account for geographical, environmental, and cultural heterogeneity. SELECTOR can be used within an approximate Bayesian computation estimation framework. We first describe the principles of SELECTOR and validate the algorithms by comparing its outputs for simple models with theoretical expectations. Then, we show how it can be used to investigate genetic differentiation of loci under balancing selection in interconnected demes with spatially heterogeneous gene flow. We identify situations in which balancing selection reduces genetic differentiation between population groups compared with neutrality and explain conflicting outcomes observed for human leukocyte antigen loci. These results and three previously published applications demonstrate that SELECTOR is efficient and robust for building insight into human settlement history and evolution

    Punctuated equilibria and 1/f noise in a biological coevolution model with individual-based dynamics

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    We present a study by linear stability analysis and large-scale Monte Carlo simulations of a simple model of biological coevolution. Selection is provided through a reproduction probability that contains quenched, random interspecies interactions, while genetic variation is provided through a low mutation rate. Both selection and mutation act on individual organisms. Consistent with some current theories of macroevolutionary dynamics, the model displays intermittent, statistically self-similar behavior with punctuated equilibria. The probability density for the lifetimes of ecological communities is well approximated by a power law with exponent near -2, and the corresponding power spectral densities show 1/f noise (flicker noise) over several decades. The long-lived communities (quasi-steady states) consist of a relatively small number of mutualistically interacting species, and they are surrounded by a ``protection zone'' of closely related genotypes that have a very low probability of invading the resident community. The extent of the protection zone affects the stability of the community in a way analogous to the height of the free-energy barrier surrounding a metastable state in a physical system. Measures of biological diversity are on average stationary with no discernible trends, even over our very long simulation runs of approximately 3.4x10^7 generations.Comment: 20 pages RevTex. Minor revisions consistent with published versio

    Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution

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    We compare and contrast the long-time dynamical properties of two individual-based models of biological coevolution. Selection occurs via multispecies, stochastic population dynamics with reproduction probabilities that depend nonlinearly on the population densities of all species resident in the community. New species are introduced through mutation. Both models are amenable to exact linear stability analysis, and we compare the analytic results with large-scale kinetic Monte Carlo simulations, obtaining the population size as a function of an average interspecies interaction strength. Over time, the models self-optimize through mutation and selection to approximately maximize a community fitness function, subject only to constraints internal to the particular model. If the interspecies interactions are randomly distributed on an interval including positive values, the system evolves toward self-sustaining, mutualistic communities. In contrast, for the predator-prey case the matrix of interactions is antisymmetric, and a nonzero population size must be sustained by an external resource. Time series of the diversity and population size for both models show approximate 1/f noise and power-law distributions for the lifetimes of communities and species. For the mutualistic model, these two lifetime distributions have the same exponent, while their exponents are different for the predator-prey model. The difference is probably due to greater resilience toward mass extinctions in the food-web like communities produced by the predator-prey model.Comment: 26 pages, 12 figures. Discussion of early-time dynamics added. J. Math. Biol., in pres

    Classes of disruptive behavior problems in referred adolescents

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    Background: Previous studies have found considerable overlap between attention/hyperactivity problems, aggressive/oppositional problems and delinquent/conduct problems in adolescents. Sampling and Methods: Mothers of 1,965 11- to 18-year-olds (1,116 boys, 849 girls), referred to mental health agencies, completed the Child Behavior Checklist (CBCL). Latent class analysis was conducted on the Attention Problems scale (representing problems with attention, impulsivity and hyperactivity), Aggressive Behavior and Rule-Breaking Behavior scales of the CBCL. Results: Six latent classes were found. One of these classes contained individuals who suffered predominantly from attention problems and to a far lesser degree from aggressive or rule-breaking behaviors. The other 5 classes represented individuals with varying degrees of attention problems, aggressive behaviors and rule-breaking behaviors. Conclusions: Contrary to previous studies, the present study indicated that, in a large referred sample, problems with attention, impulsivity and hyperactivity can be considered as a diagnostic construct that should be distinguished from aggressive or rule-breaking behaviors. However, the present study did not support the existence of diagnostic classes constituted by individuals who primarily suffer from aggressive behaviors or rule-breaking behaviors, and not from attention problems or hyperactivity. Implications of these findings for future research and clinical practice are discussed. The value of the study was limited by the use of parent reports only. Copyright © 2007 S. Karger AG
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