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• W2000818950 abstract "Evolutionary biology shares many concepts with statistical physics: both deal with populations, whether of molecules or organisms, and both seek to simplify evolution in very many dimensions. Often, methodologies have undergone parallel and independent development, as with stochastic methods in population genetics. Here, we discuss aspects of population genetics that have embraced methods from physics: non-equilibrium statistical mechanics, travelling waves and Monte-Carlo methods, among others, have been used to study polygenic evolution, rates of adaptation and range expansions. These applications indicate that evolutionary biology can further benefit from interactions with other areas of statistical physics; for example, by following the distribution of paths taken by a population through time. Evolutionary biology shares many concepts with statistical physics: both deal with populations, whether of molecules or organisms, and both seek to simplify evolution in very many dimensions. Often, methodologies have undergone parallel and independent development, as with stochastic methods in population genetics. Here, we discuss aspects of population genetics that have embraced methods from physics: non-equilibrium statistical mechanics, travelling waves and Monte-Carlo methods, among others, have been used to study polygenic evolution, rates of adaptation and range expansions. These applications indicate that evolutionary biology can further benefit from interactions with other areas of statistical physics; for example, by following the distribution of paths taken by a population through time. a probability measure of the microscopic states of a physical system that is composed of classical (i.e. not quantum) particles in thermodynamic equilibrium. This distribution has a density proportional to the factor exp(-E/kT), where E is the energy of a state, k is Boltzmann's constant and T is the absolute temperature. an equilibrium where the probability flux of the transitions between any two states is equal in either direction. In population genetics, this implies that the numbers of adaptive and deleterious substitutions have to be equal on average. a measure of the number of possible configurations of a system. The classical measure of entropy is due to Boltzmann: S = -k logΩ, where Ω is the number (or density) of microscopic states (e.g. allele frequencies) that a system can realize for a given macroscopic state (mean fitness, a quantitative variable, etc.) and k is Boltzmann's constant. Relative entropy is defined as S=−∫ψlog(ψ/φ)dp_, where the p are the microscopic states, and the sum goes over all possible realizations; ψ is the distribution of microstates, and φ is a base or reference distribution (satisfying φ = 2NVδp). However, when φ = const. we have Shannon's entropy, which is the form used in statistical physics. Entropy is also equivalent to the log-likelihood of φ (the proposed distribution), and ψ is the sampling probability of the actual distribution. a measure of how much an infinitesimal change in an unknown parameter θ affects the likelihood ψ of an observed data set, p. Fisher's information is defined as F=∫ψp;θ∂∂θlogψp;θ2dp. When the parameter θ is time, Fisher's information describes the amount of information gained through selection. a measure of adaptation defined as ϕ(t) = s(p,t)dp/dt, where s is the selection coefficient (fitness gradient) and p is the allelic frequency. Geometrically, it is the strength of fitness change (given that s is the gradient if mean fitness, W), along the direction of evolution (given by dp/dt). The cumulative fitness flux, Φ = ∫ ϕdt, is a measure of the total amount of adaptation through the history of a population. the expected gain in log-mean fitness after selection; after an analogy with the free energy of a physical system, which is the amount of work that can be done in a thermodynamic system. Free fitness (I) emerges naturally when computing the gain in entropy S after an allele or a trait underwent selection [48], and has an equivalent expression to free energy, that is, I=logW¯−S/2N (in physics, logW¯ should be replaced by E, and 2N by 1/kT; see entry for Boltzmann distribution). interference in the selective sweep of an allele, owing to the selective effects at another linked loci. Hill–Robertson interference implies that, in the presence of recombination, genotypes with multiple mutations arise more easily by recombining existing single mutations than by multiple mutation events. a formalism of nonequilibrium statistical mechanics and quantum mechanics where the description of the system emphasizes not the states of a population of entities, but the distribution of possible stochastic paths that such a population can follow. population of replicators (typically asexual) with a high genotypic variability maintained by elevated mutation rates. dynamical equations that describe the change in time the frequency p of the different types (in particular genotypes). It has the general form dp/dt = pΔW + T, where ΔW is the difference between the fitness of the type and the mean fitness, and T are the ‘transmission’ terms, that can involve mutation, migration, recombination, etc. failure to survive or reproduce owing to differences in genotype. a probability distribution that does not change in time. This is found from the diffusion equation by setting ∂ψ/∂t = 0 and solving the resulting differential equation that is independent of time. A stationary solution might not exist (e.g. if selection is changing in time in particular ways) and, if it exists, it might require detailed balance. a mathematical framework explaining the relationship between the macroscopic properties of a system, in terms of the dynamics of the microscopic variables. At equilibrium, it leads to the classical concepts of entropy, free energy and temperature, for example. Out of equilibrium, these quantities cannot be defined formally, and current research focuses on finding probabilistic measures that apply in general, but are still based on the microscopic dynamics. Based principally on the properties of stochastic processes (e.g. the diffusion equations, or path ensembles), these measures can be applied to the distribution of allele frequencies (e.g. Fisher's information and fitness flux). solutions to nonlinear differential equations characterized by functions that are of stable shape, and move at a certain velocity either in physical space, or in genetic space. (Travelling waves are also known as solitons in the physics and mathematics literature.) Scheme where individuals that have traits outside a prescribed range are eliminated. This type of selection is popular in artificial selection." @default.
• W2000818950 created "2016-06-24" @default.
• W2000818950 creator A5011755952 @default.
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• W2000818950 date "2011-08-01" @default.
• W2000818950 modified "2023-10-18" @default.
• W2000818950 title "The contribution of statistical physics to evolutionary biology" @default.
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• W2000818950 doi "https://doi.org/10.1016/j.tree.2011.04.002" @default.
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