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Guide to Simulation and Modeling for Biosciences

  • Textbook
  • © 2015

Overview

  • Presents a broad overview of the most important techniques used to model biological systems
  • Provides a detailed introduction to agent-based models, stochastic modeling techniques, and spatial simulations for the novice modeler
  • With exercises, and a companion website featuring downloadable sample code
  • Includes supplementary material: sn.pub/extras

Part of the book series: Simulation Foundations, Methods and Applications (SFMA)

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Table of contents (8 chapters)

Keywords

About this book

This accessible text presents a detailed introduction to the use of a wide range of software tools and modeling environments for use in the biosciences, as well as the fundamental mathematical background. The practical constraints presented by each modeling technique are described in detail, enabling the researcher to determine which software package would be most useful for a particular problem. 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, spatial simulations, and Gillespie’s stochastic simulation algorithm; provides exercises; describes such useful tools as the Maxima algebra system, the PRISM model checker, and the modeling environments Repast Simphony and Smoldyn; contains appendices on rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts; offers supplementary material at an associated website.

Authors and Affiliations

  • University of Kent, Canterbury, United Kingdom

    David J. Barnes

  • School of Computing, University of Kent, Canterbury, United Kingdom

    Dominique Chu

About the authors

David J. Barnes is a senior lecturer in computer science at the University of Kent, UK, with a strong background in the teaching of programming and the implementation of computational models of biological systems.

Dominique Chu is a senior lecturer in computer science at the University of Kent, UK. He is an expert in mathematical and computational modeling of biological systems, with years of experience in these fields.

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