Literature DB >> 29944856

Mathematical models for chemotaxis and their applications in self-organisation phenomena.

Kevin J Painter1.   

Abstract

Chemotaxis is a fundamental guidance mechanism of cells and organisms, responsible for attracting microbes to food, embryonic cells into developing tissues, immune cells to infection sites, animals towards potential mates, and mathematicians into biology. The Patlak-Keller-Segel (PKS) system forms part of the bedrock of mathematical biology, a go-to-choice for modellers and analysts alike. For the former it is simple yet recapitulates numerous phenomena; the latter are attracted to these rich dynamics. Here I review the adoption of PKS systems when explaining self-organisation processes. I consider their foundation, returning to the initial efforts of Patlak and Keller and Segel, and briefly describe their patterning properties. Applications of PKS systems are considered in their diverse areas, including microbiology, development, immunology, cancer, ecology and crime. In each case a historical perspective is provided on the evidence for chemotactic behaviour, followed by a review of modelling efforts; a compendium of the models is included as an Appendix. Finally, a half-serious/half-tongue-in-cheek model is developed to explain how cliques form in academia. Assumptions in which scholars alter their research line according to available problems leads to clustering of academics and the formation of "hot" research topics. Crown
Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bacteria; Development; Ecology; Pathology; Patlak–Keller–Segel; Pattern formation; Slime molds; Social clique formation; Social sciences

Year:  2018        PMID: 29944856     DOI: 10.1016/j.jtbi.2018.06.019

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  12 in total

1.  From a discrete model of chemotaxis with volume-filling to a generalized Patlak-Keller-Segel model.

Authors:  Federica Bubba; Tommaso Lorenzi; Fiona R Macfarlane
Journal:  Proc Math Phys Eng Sci       Date:  2020-05-13       Impact factor: 2.704

2.  ChemChaste: Simulating spatially inhomogeneous biochemical reaction-diffusion systems for modeling cell-environment feedbacks.

Authors:  Connah G M Johnson; Alexander G Fletcher; Orkun S Soyer
Journal:  Gigascience       Date:  2022-06-17       Impact factor: 7.658

Review 3.  The ecological roles of bacterial chemotaxis.

Authors:  Johannes M Keegstra; Francesco Carrara; Roman Stocker
Journal:  Nat Rev Microbiol       Date:  2022-03-15       Impact factor: 78.297

4.  Collective self-optimization of communicating active particles.

Authors:  Alexandra V Zampetaki; Benno Liebchen; Alexei V Ivlev; Hartmut Löwen
Journal:  Proc Natl Acad Sci U S A       Date:  2021-12-07       Impact factor: 12.779

5.  The impact of rheotaxis and flow on the aggregation of organisms.

Authors:  K J Painter
Journal:  J R Soc Interface       Date:  2021-10-20       Impact factor: 4.293

6.  A traveling-wave solution for bacterial chemotaxis with growth.

Authors:  Avaneesh V Narla; Jonas Cremer; Terence Hwa
Journal:  Proc Natl Acad Sci U S A       Date:  2021-11-30       Impact factor: 12.779

7.  Multi-Cue Kinetic Model with Non-Local Sensing for Cell Migration on a Fiber Network with Chemotaxis.

Authors:  Martina Conte; Nadia Loy
Journal:  Bull Math Biol       Date:  2022-02-12       Impact factor: 1.758

Review 8.  Mathematical models of neuronal growth.

Authors:  Hadrien Oliveri; Alain Goriely
Journal:  Biomech Model Mechanobiol       Date:  2022-01-07

9.  Swarm Hunting and Cluster Ejections in Chemically Communicating Active Mixtures.

Authors:  Jens Grauer; Hartmut Löwen; Avraham Be'er; Benno Liebchen
Journal:  Sci Rep       Date:  2020-03-27       Impact factor: 4.379

Review 10.  A "Numerical Evo-Devo" Synthesis for the Identification of Pattern-Forming Factors.

Authors:  Richard Bailleul; Marie Manceau; Jonathan Touboul
Journal:  Cells       Date:  2020-08-05       Impact factor: 6.600

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