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Idealised population models could not only provide us with information about present populations conditions but are useful in revealing natural history and population dynamics in the past as well. Using an idealised population model, Anders
Eriksson and Andrea Manica (2012) tested the hypothesis of
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In 1908, G. H. Hardy and
Wilhelm Weinberg modeled an idealised population to demonstrate that in the absence of selection, migration, random genetic drift, allele frequencies stay constant over time, and that in the presence of random mating, genotype frequencies are related to allele frequencies
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1:1, and then multiply by mitochondrial genes substitution rate, per generation. Making several assumptions according to the sex ratio and number of juveniles, they were able to calculate that in contrast to historical records, modern whale populations are far from harvestable range.
135:. The authors compare genome sequences of two human populations, Neanderthals and chimpanzee. Eriksson and Manica created a stepping stone model under which Africa and Eurasia are represented as a string of equal size populations. They concluded that under the
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is one that can be described using a number of simplifying assumptions. Models of idealised populations are either used to make a general point, or they are fit to data on real populations for which the assumptions may not hold true. For example,
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Eriksson, Anders, and Andrea Manica. "Effect of ancient population structure on the degree of polymorphism shared between modern human populations and ancient hominins." Proceedings of the
National Academy of Sciences 109, no. 35 (2012):
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that is capable of simulating simultaneous evolution of populations based on Fisher-Wright model. Idealised population model also, could be used in several simple simulations designed for education. So,
139:, in which Europeans can exchange genetic information with Asians and not with Africans, similarities between Neanderthal genome and Eurasian could be explained by ancient populations structure.
72:, rather than the non-overlapping generations of the Fisher-Wright model. The complexities of real populations can cause their behavior to match an idealised population with an
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data, they questioned: have populations of North
Atlantic great whales recovered enough for commercial whaling? To calculate genetic diversity the authors multiply long term
184:. Nielsen, Rasmus, and Montgomery Slatkin. An Introduction to Population Genetics: Theory and Applications. Sunderland, MA: Sinauer Associates, 2013. Print.
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is used to fit data to models of idealised populations. The most common idealized population in population genetics is described in the
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simulator (Requires an updated Java version), which is designed to visualize influence of genetic drift on natural populations.
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A good example of usage idealised population model, in tracking natural population conditions, could be found in a research of
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193:.Crow, James F. "Population genetics history: a personal view." Annual Review of Genetics 21, no. 1 (1987): 1-22.
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Simulation is designed to introduce general public to the concept of natural selection. Another example is
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that is very different from the census population size of the real population. For sexual
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Philosophical
Transactions of the Royal Society B: Biological Sciences
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Hanage, W. P.; Spratt, B. G.; Turner, K. M. E.; Fraser, C. (2006).
212:"Whales before whaling in the North Atlantic"
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64:with any other member. Another example is a
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56:have constant size, and their members can
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147:Usage of models, also allows to perform
52:(1922, 1930) and (1931). Wright-Fisher
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117:size of the females by two, assuming
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126:Application to population history
283:"Modelling bacterial speciation"
162:Charles Darwin: Can you survive?
93:called the Hardy-Weinberg law.
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97:Usage in population dynamics
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91:binomial square principle
74:effective population size
68:, which has overlapping
18:Fisher-Wright population
251:10.1126/science.1084524
299:10.1098/rstb.2006.1926
339:Statistical genetics
143:Computer simulations
137:stepping stone model
115:effective population
33:idealised population
334:Population genetics
293:(1475): 2039–2044.
233:2003Sci...301..508R
208:Palumbi, Stephen R.
42:Wright-Fisher model
29:population genetics
107:Stephen R. Palumbi
227:(5632): 508–510.
111:genetic diversity
38:coalescent theory
16:(Redirected from
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149:simulations
70:generations
66:Moran model
54:populations
328:Categories
204:Roman, Joe
172:References
155:is a free
237:CiteSeerX
119:sex ratio
103:Joe Roman
62:reproduce
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210:(2003).
78:diploids
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229:Bibcode
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