Literature DB >> 23533292

Mathematical modelling in developmental biology.

Olga Vasieva1, Manan'Iarivo Rasolonjanahary, Bakhtier Vasiev.   

Abstract

In recent decades, molecular and cellular biology has benefited from numerous fascinating developments in experimental technique, generating an overwhelming amount of data on various biological objects and processes. This, in turn, has led biologists to look for appropriate tools to facilitate systematic analysis of data. Thus, the need for mathematical techniques, which can be used to aid the classification and understanding of this ever-growing body of experimental data, is more profound now than ever before. Mathematical modelling is becoming increasingly integrated into biological studies in general and into developmental biology particularly. This review outlines some achievements of mathematics as applied to developmental biology and demonstrates the mathematical formulation of basic principles driving morphogenesis. We begin by describing a mathematical formalism used to analyse the formation and scaling of morphogen gradients. Then we address a problem of interplay between the dynamics of morphogen gradients and movement of cells, referring to mathematical models of gastrulation in the chick embryo. In the last section, we give an overview of various mathematical models used in the study of the developmental cycle of Dictyostelium discoideum, which is probably the best example of successful mathematical modelling in developmental biology.

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Year:  2013        PMID: 23533292     DOI: 10.1530/REP-12-0081

Source DB:  PubMed          Journal:  Reproduction        ISSN: 1470-1626            Impact factor:   3.906


  4 in total

1.  Mathematical modeling of the interaction between yolk utilization and fish growth in zebrafish, Danio rerio.

Authors:  Ashley V Schwartz; Karilyn E Sant; Julian Navarrete; Uduak Z George
Journal:  Development       Date:  2021-05-07       Impact factor: 6.868

2.  Modelling Chemotactic Motion of Cells in Biological Tissues.

Authors:  Bakhtier Vasiev
Journal:  PLoS One       Date:  2016-10-31       Impact factor: 3.240

3.  Modeling protein dynamics in Caenorhabditis elegans embryos reveals that the PLK-1 gradient relies on weakly coupled reaction-diffusion mechanisms.

Authors:  Sofia Barbieri; Aparna Nurni Ravi; Erik E Griffin; Monica Gotta
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-08       Impact factor: 12.779

4.  Scaling of morphogenetic patterns in reaction-diffusion systems.

Authors:  Manan'Iarivo Rasolonjanahary; Bakhtier Vasiev
Journal:  J Theor Biol       Date:  2016-05-31       Impact factor: 2.691

  4 in total

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