book cover

Guide to Simulation and Modeling for Biosciences (2nd edition),
David J. Barnes and Dominique Chu,
Springer, September 2015.
ISBN: 978-1-4471-6761-7 (Print) 978-1-4471-6762-4 (Online), 2015.

David   Dominique

Supporting Material


Computational modeling has become an essential tool for researchers in the biological sciences. Yet in biological modeling, there is no one technique that is suitable for all problems. Instead, different problems call for different approaches. Furthermore, it can be helpful to analyze the same system using a variety of approaches, to be able to exploit the advantages and drawbacks of each. In practice, it is often unclear which modeling approaches will be most suitable for a particular biological question - a problem that requires researchers to know a reasonable amount about a number of techniques, rather than become experts on a single one.

Guide to Simulation and Modeling for Biosciences addresses this issue by presenting a broad overview of the most important techniques used to model biological systems. In addition to providing an introduction into the use of a wide range of software tools and modeling environments, this helpful text/reference describes the constraints and difficulties that each modeling technique presents in practice. This enables the researcher to quickly determine which software package would be most useful for their particular problem.

This unique and practical work guides the novice modeler through realistic and concrete modeling projects, highlighting and commenting on the process of abstracting the real system into a model. Students and active researchers in the biosciences will also benefit from the discussions of the high-quality, tried-and-tested modeling tools described in the book, as well as thorough descriptions and examples.


Topics and features:

  • Introduces a basic array of techniques to formulate models of biological systems, and to solve them.

  • Discusses agent-based models, stochastic modeling techniques, differential equations and Gillespie's stochastic simulation algorithm.

  • Intersperses the text with exercises.

  • Includes practical introductions to the Maxima computer algebra system, the PRISM model checker, and the Repast Simphony agent modeling environment.

  • Contains appendices on Repast batch running, rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts.

  • Supplies source code for many of the example models discussed, at the associated website

Chapter Organization

Source Code

Source of all the associated material in GZIP/TAR format and ZIP format.

Date of latest version: 18th September 2015.

The source code comprises the following:

All materials © Springer, David J. Barnes and Dominique Chu, 2010-2015.

Please notify us of any errors or inaccuracies at the address below.


We would welcome notification of corrections from our readers and will aim to publish them here.

Links to Modeling Software

This section contains links to both free and commercial software and packages that may be of use to modelers. Most of these are mentioned in the book, but not all are covered in detail.

This page ( is maintained by: David J. Barnes (the anti-spam email address will need editing by you) to whom any questions, comments and corrections should be addressed.

© David J. Barnes and Dominique Chu

Last Updated: 18th September 2015
Created: 29th June 2010