Sentence examples for mathematical population from inspiring English sources

The neo-Darwinian synthesis of 19th-century natural selection with 20th-century mathematical population genetics, orchestrated by Ernst Mayr, one of Mr Gould's senior colleagues at Harvard, was coming to power.

In this work a first attempt is made to incooperate these ideas into a mathematical population model using two internal particle properties.

Though he gradually toned down this aspect of his work, a significant school of mathematical population geneticists in the 1960s and 70s took these ideas and ran with them, developing a 'Neutralist' approach to evolutionary change.

One of the more spectacular events in the history of twentieth-century biology as a discipline, triggered by the rise of genetics (mathematical population genetics in particular), was the so-called "modern evolutionary synthesis".

Without loss of generality, we also assume that ([0,omega)_{mathbb{T}}cap{t_{k}: kinmathbb{Z}}={ t_{1},ldots,t_{p}}t_{p}}). System (1.1) contain many mathematical population models of differential equations and difference equations.

On the other hand, mathematical population geneticists like Ronald A. Fisher, J. B. S. Haldane, and Sewall Wright could make use of the classical gene with equal rigor and precision to elaborate testable mathematical models describing the effects of evolutionary factors like selection and mutation on the genetic composition of populations (Provine 1971).

Its combination with multivalued analysis opens new horizons in exploring more realistic models in mathematical economics, population dynamics and optimal control theory (see e.g. [1, 2]).

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].

The effect of each of these evolutionary forces on genetic variation within and among populations has been developed in great detail in the mathematical theory of population genetics founded on the seminal works of Fisher, Wright, and Haldane.

To address these questions, we calculated, using mathematical modelling, the population log10 viral load in a representative nation in SSA, Tanzania, to examine population viral load variation from the start of the epidemic up to today, and its future evolution with ART scale-up.

Mathematical models for population outgrowth and interactions have been developed early on [ 108], but usually the fluctuations in populations are represented using simple line graphs that indicate the population spread over time.