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Mathematical model for adaptive evolution of populations based on a complex domain

A mutation is ultimately essential for adaptive evolution in all populations. It arises all the time, but is mostly fixed by enzymes. Further, most do consider that the evolution mechanism is by a natural assortment of variations in organisms in line for random variations in their DNA, and the sugge...

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Autores principales: Ibrahim, Rabha W., Ahmad, M.Z., Al-Janaby, Hiba F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4705264/
https://www.ncbi.nlm.nih.gov/pubmed/26858564
http://dx.doi.org/10.1016/j.sjbs.2015.09.012
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author Ibrahim, Rabha W.
Ahmad, M.Z.
Al-Janaby, Hiba F.
author_facet Ibrahim, Rabha W.
Ahmad, M.Z.
Al-Janaby, Hiba F.
author_sort Ibrahim, Rabha W.
collection PubMed
description A mutation is ultimately essential for adaptive evolution in all populations. It arises all the time, but is mostly fixed by enzymes. Further, most do consider that the evolution mechanism is by a natural assortment of variations in organisms in line for random variations in their DNA, and the suggestions for this are overwhelming. The altering of the construction of a gene, causing a different form that may be communicated to succeeding generations, produced by the modification of single base units in DNA, or the deletion, insertion, or rearrangement of larger units of chromosomes or genes. This altering is called a mutation. In this paper, a mathematical model is introduced to this reality. The model describes the time and space for the evolution. The tool is based on a complex domain for the space. We show that the evolution is distributed with the hypergeometric function. The Boundedness of the evolution is imposed by utilizing the Koebe function.
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spelling pubmed-47052642016-02-08 Mathematical model for adaptive evolution of populations based on a complex domain Ibrahim, Rabha W. Ahmad, M.Z. Al-Janaby, Hiba F. Saudi J Biol Sci Original Article A mutation is ultimately essential for adaptive evolution in all populations. It arises all the time, but is mostly fixed by enzymes. Further, most do consider that the evolution mechanism is by a natural assortment of variations in organisms in line for random variations in their DNA, and the suggestions for this are overwhelming. The altering of the construction of a gene, causing a different form that may be communicated to succeeding generations, produced by the modification of single base units in DNA, or the deletion, insertion, or rearrangement of larger units of chromosomes or genes. This altering is called a mutation. In this paper, a mathematical model is introduced to this reality. The model describes the time and space for the evolution. The tool is based on a complex domain for the space. We show that the evolution is distributed with the hypergeometric function. The Boundedness of the evolution is imposed by utilizing the Koebe function. Elsevier 2016-01 2015-09-11 /pmc/articles/PMC4705264/ /pubmed/26858564 http://dx.doi.org/10.1016/j.sjbs.2015.09.012 Text en © 2015 Production and hosting by Elsevier B.V. on behalf of King Saud University. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Ibrahim, Rabha W.
Ahmad, M.Z.
Al-Janaby, Hiba F.
Mathematical model for adaptive evolution of populations based on a complex domain
title Mathematical model for adaptive evolution of populations based on a complex domain
title_full Mathematical model for adaptive evolution of populations based on a complex domain
title_fullStr Mathematical model for adaptive evolution of populations based on a complex domain
title_full_unstemmed Mathematical model for adaptive evolution of populations based on a complex domain
title_short Mathematical model for adaptive evolution of populations based on a complex domain
title_sort mathematical model for adaptive evolution of populations based on a complex domain
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4705264/
https://www.ncbi.nlm.nih.gov/pubmed/26858564
http://dx.doi.org/10.1016/j.sjbs.2015.09.012
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