Literature DB >> 15868200

Calculating spatial statistics for velocity jump processes with experimentally observed reorientation parameters.

E A Codling1, N A Hill.   

Abstract

Mathematical modelling of the directed movement of animals, microorganisms and cells is of great relevance in the fields of biology and medicine. Simple diffusive models of movement assume a random walk in the position, while more realistic models include the direction of movement by assuming a random walk in the velocity. These velocity jump processes, although more realistic, are much harder to analyse and an equation that describes the underlying spatial distribution only exists in one dimension. In this communication we set up a realistic reorientation model in two dimensions, where the mean turning angle is dependent on the previous direction of movement and bias is implicitly introduced in the probability distribution for the direction of movement. This model, and the associated reorientation parameters, is based on data from experiments on swimming microorganisms. Assuming a transport equation to describe the motion of a population of random walkers using a velocity jump process, together with this realistic reorientation model, we use a moment closure method to derive and solve a system of equations for the spatial statistics. These asymptotic equations are a very good match to simulated random walks for realistic parameter values.

Mesh:

Year:  2005        PMID: 15868200     DOI: 10.1007/s00285-005-0317-7

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


  6 in total

1.  A biased random walk model for the trajectories of swimming micro-organisms.

Authors:  N A Hill; D P Hader
Journal:  J Theor Biol       Date:  1997-06-21       Impact factor: 2.691

2.  Cattaneo models for chemosensitive movement. Numerical solution and pattern formation.

Authors:  Y Dolak; T Hillen
Journal:  J Math Biol       Date:  2003-02       Impact factor: 2.259

3.  Sampling rate effects on measurements of correlated and biased random walks.

Authors:  E A Codling; N A Hill
Journal:  J Theor Biol       Date:  2004-12-15       Impact factor: 2.691

4.  Measurement of bacterial random motility and chemotaxis coefficients: II. Application of single-cell-based mathematical model.

Authors:  R M Ford; D A Lauffenburger
Journal:  Biotechnol Bioeng       Date:  1991-03-25       Impact factor: 4.530

5.  Analyzing insect movement as a correlated random walk.

Authors:  P M Kareiva; N Shigesada
Journal:  Oecologia       Date:  1983-02       Impact factor: 3.225

6.  Models of dispersal in biological systems.

Authors:  H G Othmer; S R Dunbar; W Alt
Journal:  J Math Biol       Date:  1988       Impact factor: 2.259

  6 in total
  2 in total

Review 1.  Random walk models in biology.

Authors:  Edward A Codling; Michael J Plank; Simon Benhamou
Journal:  J R Soc Interface       Date:  2008-08-06       Impact factor: 4.118

2.  The impact of temporal sampling resolution on parameter inference for biological transport models.

Authors:  Jonathan U Harrison; Ruth E Baker
Journal:  PLoS Comput Biol       Date:  2018-06-25       Impact factor: 4.475

  2 in total

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