The most recent version of the manuscript can be downloaded here: pdf file . This manuscript has been extended to a book published by the Cambridge University Press in 2019/2020 (see below), with the corresponding computer codes available here.

Computer codes which were used to compute the illustrative results from this paper can be downloaded below. Computations from Sections 2, 3 and (partially) 5 were done in Matlab. A Matlab file "FigureX.m" plots the corresponding Figure X in the paper. Computations from Section 4 and Figure 5.4 were done in Fortran 90. A Fortran 90 code "FortranFigureX.f90" stores the computed data in the corresponding data file "FigureX.dat" which is plotted (visualized) in Matlab using the Matlab file "FigureX.m". All codes were successfully tested on both, Unix and MS Windows, versions of Matlab. Comments and suggestions can be sent to my e-mail.

Note (June 2018): The original computer codes (below) were written in 2007. They still work. However, Matlab has updated its command for annotating figure legends, which has affected the visualization of results in Figures 2_2(a) and 2.3 (using most recent versions of Matlab). The updated Matlab codes are provided below, next to the corresponding 2007 versions. The computations are the same in both 2007 and 2018 codes. They only differ in the syntax of a command for annotating plots.

Section 2

Figure 2.1: Figure2_1a.m, Figure2_1b.m (Matlab files)
Figure 2.2: Figure2_2a.m, Figure2_2b.m (Matlab files) Figure2_2a_2018.m (2018 update)
Figure 2.3: Figure2_3.m (Matlab file) Figure2_3_2018.m (2018 update)
Figure 2.4: Figure2_4.m (Matlab file)

Section 3

Figure 3.1: Figure3_1.m (Matlab file)
Figure 3.2: Figure3_2a.m, Figure3_2b.m (Matlab files)
Figure 3.3: Figure3_3a.m, Figure3_3b.m (Matlab files)

Section 4

Figure 4.1: Figure4_1.m (Matlab file), dataFigure4_1.dat (data file), FortranFigure4_1.f90 (Fortran 90 file)
Figure 4.2: Figure4_2.m (Matlab file), dataFigure4_2.dat (data file), FortranFigure4_2.f90 (Fortran 90 file)
Figure 4.3: Figure4_3.m (Matlab file), dataFigure4_3.dat (data file), FortranFigure4_3.f90 (Fortran 90 file)

Section 5

Figure 5.1: Figure5_1a.m, Figure5_1b.m (Matlab files)
Figure 5.2: Figure5_2.m (Matlab file)
Figure 5.3: Figure5_3.m (Matlab file)
Figure 5.4: Figure5_4.m (Matlab file), dataFigure5_4.dat (data file), FortranFigure5_4.f90 (Fortran 90 file)

New Book

Radek Erban and Jonathan Chapman, "Stochastic Modelling of Reaction-Diffusion Processes", Cambridge Texts in Applied Mathematics, Cambridge University Press, 308 pages (2019)

Our new book provides an introduction to stochastic methods for modelling biological systems, covering a number of applications, ranging in size from molecular dynamics simulations of small biomolecules to stochastic modelling of groups of animals. The focus is on the underlying mathematics, i.e. it is not assumed that the reader took any advanced courses in biology or chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate or beginning graduate-level courses in applied mathematics. It discusses the essence of mathematical methods which appear (under different names) in a number of interdisciplinary scientific fields bridging mathematics and computations with biology and chemistry. New mathematical approaches and their analysis are explained using simple examples of biological models. The book starts with stochastic modelling of chemical reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio-temporal models are then studied, including models of diffusion and stochastic reaction-diffusion modelling. The methods covered include molecular dynamics, Brownian dynamics, velocity jump processes and compartment-based models. [download the table of contents] Computer codes are available here.