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Many population models with random interference have been investigated [55 60].
Among many population models, the neutral logarithmic population model has recently attracted the attention of many mathematicians and biologists.
Predictions in this regime can be considered universal in the sense that many population models exhibit equivalent behavior in the diffusion limit.
More broadly, many population models in ecology implicitly recognize the importance of accounting for storage mechanisms to describe the dynamics of individual organisms.
In mathematical literature, many population models have been considered, from deterministic and stochastic population models, where the population size is represented by a discrete random variable, to very complex continuous stochastic models [1 3].
In addition, many population models [60 62] are often associated with a functional response, which refers to the predation rate per predator as a function of prey density [63, 64] and predator density [65 67].
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Transition matrices M resulting from this model are generally square, due to the fixed population size (a common feature of many population genetic models, compare [ 3]).
The rigorous nature of many population genetics models and their extensive analysis has lead to key insights in analysing genomic sequences [ 2, 60- 64].
As is common in many population genetic models, we assume an infinite population and consider this population subject to frequent sublethal deleterious mutations that act independently from one another in reducing fitness.
Many population PK models have found patient demographic factors, such as age, body weight and gender, and also receptor number and disease-related factors, such as number of metastatic sites, circulating tumour receptors and tumour burden, to have a statistically significant impact on PK (Bruno et al, 2005; Gupta et al, 2012; Zhu et al, 2014).
Dispersal is a fundamental component of many spatial population models.
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many aging models
many population centers
many population types
many population centres
many population experts
many population groups
many home models
many population studies
many population genetics
many population doublings
many role models
many population segments
many population analyses
many population trends
many population surveys
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