Literature DB >> 18626644

A user's guide to PDE models for chemotaxis.

T Hillen1, K J Painter.   

Abstract

Mathematical modelling of chemotaxis (the movement of biological cells or organisms in response to chemical gradients) has developed into a large and diverse discipline, whose aspects include its mechanistic basis, the modelling of specific systems and the mathematical behaviour of the underlying equations. The Keller-Segel model of chemotaxis (Keller and Segel in J Theor Biol 26:399-415, 1970; 30:225-234, 1971) has provided a cornerstone for much of this work, its success being a consequence of its intuitive simplicity, analytical tractability and capacity to replicate key behaviour of chemotactic populations. One such property, the ability to display "auto-aggregation", has led to its prominence as a mechanism for self-organisation of biological systems. This phenomenon has been shown to lead to finite-time blow-up under certain formulations of the model, and a large body of work has been devoted to determining when blow-up occurs or whether globally existing solutions exist. In this paper, we explore in detail a number of variations of the original Keller-Segel model. We review their formulation from a biological perspective, contrast their patterning properties, summarise key results on their analytical properties and classify their solution form. We conclude with a brief discussion and expand on some of the outstanding issues revealed as a result of this work.

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Year:  2008        PMID: 18626644     DOI: 10.1007/s00285-008-0201-3

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  59 in total

1.  A new interpretation of the Keller-Segel model based on multiphase modelling.

Authors:  Helen M Byrne; Markus R Owen
Journal:  J Math Biol       Date:  2004-07-05       Impact factor: 2.259

2.  Complex patterns formed by motile cells of Escherichia coli.

Authors:  E O Budrene; H C Berg
Journal:  Nature       Date:  1991-02-14       Impact factor: 49.962

3.  Dynamics of formation of symmetrical patterns by chemotactic bacteria.

Authors:  E O Budrene; H C Berg
Journal:  Nature       Date:  1995-07-06       Impact factor: 49.962

4.  Model for the chemotactic response of a bacterial population.

Authors:  I R Lapidus; R Schiller
Journal:  Biophys J       Date:  1976-07       Impact factor: 4.033

5.  Model for chemotaxis.

Authors:  E F Keller; L A Segel
Journal:  J Theor Biol       Date:  1971-02       Impact factor: 2.691

Review 6.  The great escape: when cancer cells hijack the genes for chemotaxis and motility.

Authors:  John Condeelis; Robert H Singer; Jeffrey E Segall
Journal:  Annu Rev Cell Dev Biol       Date:  2005       Impact factor: 13.827

7.  Chemotaxis and chemokinesis in eukaryotic cells: the Keller-Segel equations as an approximation to a detailed model.

Authors:  J A Sherratt
Journal:  Bull Math Biol       Date:  1994-01       Impact factor: 1.758

8.  Incorporation of receptor kinetics into a model for bacterial chemotaxis.

Authors:  L A Segel
Journal:  J Theor Biol       Date:  1976-03       Impact factor: 2.691

9.  Localized bacterial infection in a distributed model for tissue inflammation.

Authors:  D A Lauffenburger; C R Kennedy
Journal:  J Math Biol       Date:  1983       Impact factor: 2.259

10.  A stochastic model for leukocyte random motility and chemotaxis based on receptor binding fluctuations.

Authors:  R T Tranquillo; D A Lauffenburger; S H Zigmond
Journal:  J Cell Biol       Date:  1988-02       Impact factor: 10.539

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  74 in total

1.  Spiky and transition layer steady states of chemotaxis systems via global bifurcation and Helly's compactness theorem.

Authors:  Xuefeng Wang; Qian Xu
Journal:  J Math Biol       Date:  2012-04-18       Impact factor: 2.259

2.  Classification and stability of global inhomogeneous solutions of a macroscopic model of cell motion.

Authors:  Richard Gejji; Bogdan Kazmierczak; Mark Alber
Journal:  Math Biosci       Date:  2012-04-13       Impact factor: 2.144

3.  Modeling local interactions during the motion of cyanobacteria.

Authors:  Amanda Galante; Susanne Wisen; Devaki Bhaya; Doron Levy
Journal:  J Theor Biol       Date:  2012-06-17       Impact factor: 2.691

4.  Large mass self-similar solutions of the parabolic-parabolic Keller-Segel model of chemotaxis.

Authors:  Piotr Biler; Lucilla Corrias; Jean Dolbeault
Journal:  J Math Biol       Date:  2010-08-22       Impact factor: 2.259

5.  SpringSaLaD: A Spatial, Particle-Based Biochemical Simulation Platform with Excluded Volume.

Authors:  Paul J Michalski; Leslie M Loew
Journal:  Biophys J       Date:  2016-02-02       Impact factor: 4.033

6.  Mathematical modeling of cancer cell invasion of tissue: biological insight from mathematical analysis and computational simulation.

Authors:  Vivi Andasari; Alf Gerisch; Georgios Lolas; Andrew P South; Mark A J Chaplain
Journal:  J Math Biol       Date:  2010-09-26       Impact factor: 2.259

7.  A multiscale hybrid mathematical model of epidermal-dermal interactions during skin wound healing.

Authors:  Yangyang Wang; Christian F Guerrero-Juarez; Yuchi Qiu; Huijing Du; Weitao Chen; Seth Figueroa; Maksim V Plikus; Qing Nie
Journal:  Exp Dermatol       Date:  2019-04       Impact factor: 3.960

8.  Towards an integrated experimental-theoretical approach for assessing the mechanistic basis of hair and feather morphogenesis.

Authors:  K J Painter; G S Hunt; K L Wells; J A Johansson; D J Headon
Journal:  Interface Focus       Date:  2012-02-15       Impact factor: 3.906

9.  Modeling selective local interactions with memory.

Authors:  Amanda Galante; Doron Levy
Journal:  Physica D       Date:  2013-10-01       Impact factor: 2.300

10.  Traveling wave solutions from microscopic to macroscopic chemotaxis models.

Authors:  Roger Lui; Zhi An Wang
Journal:  J Math Biol       Date:  2010-11       Impact factor: 2.259

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