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On the inclusion of self regulating branching processes in the working paradigm of evolutionary and population genetics

Overview of attention for article published in Frontiers in Genetics, January 2013
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Title
On the inclusion of self regulating branching processes in the working paradigm of evolutionary and population genetics
Published in
Frontiers in Genetics, January 2013
DOI 10.3389/fgene.2013.00011
Pubmed ID
Authors

Charles J. Mode, Candace K. Sleeman, Towfique Raj

Abstract

The principal goal of this methodological paper is to suggest to a general audience in the genetics community that the consideration of recent developments of self regulating branching processes may lead to the possibility of including this class of stochastic processes as part of working paradigm of evolutionary and population genetics. This class of branching processes is self regulating in the sense that an evolving population will grow only to a total population size that can be sustained by the environment. From the mathematical point of view the class processes under consideration belongs to a subfield of probability and statistics sometimes referred to as computational applied probability and stochastic processes. Computer intensive methods based on Monte Carlo simulation procedures have been used to empirically work out the predictions of a formulation by assigning numerical values to some point in the parameter space and computing replications of realizations of the process over thousands of generations of evolution. Statistical methods are then used on such samples of simulated data to produce informative summarizations of the data that provide insights into the evolutionary implications of computer experiments. Briefly, it is also possible to embed deterministic non-linear difference equations in the stochastic process by using a statistical procedure to estimate the sample functions of the process, which has interesting methodological implications as to whether stochastic or deterministic formulations may be applied separately or in combination in the study of evolution. It is recognized that the literature on population genetics contains a substantial number of papers in which Monte Carlo simulation methods have been used. But, this extensive literature is beyond the scope of this paper, which is focused on potential applications of self regulating branching processes in evolutionary and population genetics.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 35%
Researcher 3 18%
Professor 2 12%
Student > Master 2 12%
Professor > Associate Professor 2 12%
Other 2 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 65%
Mathematics 2 12%
Linguistics 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Computer Science 1 6%
Other 1 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 February 2013.
All research outputs
#20,182,546
of 22,696,971 outputs
Outputs from Frontiers in Genetics
#8,522
of 11,755 outputs
Outputs of similar age
#248,720
of 280,682 outputs
Outputs of similar age from Frontiers in Genetics
#263
of 319 outputs
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