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Cellular Automaton Modeling of Biological Pattern Formation

Characterization, Examples, and Analysis

  • Andreas Deutsch
  • Sabine Dormann

Table of contents

  1. Front Matter
    Pages i-xxii
  2. General Principles and Models of Pattern Formation

    1. Front Matter
      Pages 1-1
    2. Andreas Deutsch, Sabine Dormann
      Pages 3-11
    3. Andreas Deutsch, Sabine Dormann
      Pages 13-47
    4. Andreas Deutsch, Sabine Dormann
      Pages 49-61
  3. Cellular Automaton Modeling

    1. Front Matter
      Pages 63-63
    2. Andreas Deutsch, Sabine Dormann
      Pages 65-111
  4. Applications

    1. Front Matter
      Pages 113-113
    2. Andreas Deutsch, Sabine Dormann
      Pages 115-140
    3. Andreas Deutsch, Sabine Dormann
      Pages 141-158
    4. Andreas Deutsch, Sabine Dormann
      Pages 159-183
    5. Andreas Deutsch, Sabine Dormann
      Pages 185-202
    6. Andreas Deutsch, Sabine Dormann
      Pages 203-217
    7. Andreas Deutsch, Sabine Dormann
      Pages 219-230
    8. Andreas Deutsch, Sabine Dormann
      Pages 231-255
    9. Andreas Deutsch, Sabine Dormann
      Pages 257-292
    10. Andreas Deutsch, Sabine Dormann
      Pages 293-345
    11. Andreas Deutsch, Sabine Dormann
      Pages 347-361
  5. Back Matter
    Pages 363-464

About this book

Introduction

This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field.

The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In the final chapter, the authors critically discuss possibilities and limitations of the cellular automaton approach in modeling various biological applications, along with future research directions. Suggestions for research projects are provided throughout the book to encourage additional engagement with the material, and an accompanying simulator is available for readers to perform their own simulations on several of the models covered in the text.

With its accessible presentation and interdisciplinary approach, Cellular Automaton Modeling of Biological Pattern Formation is suitable for graduate and advanced undergraduate students in mathematical biology, biological modeling, and biological computing.
It will also be a valuable resource for researchers and practitioners in applied mathematics, mathematical biology, computational physics, bioengineering, and computer science.
 
PRAISE FOR THE FIRST EDITION

An ideal guide for someone with a mathematical or physical background to start exploring biological modelling. Importantly, it will also serve as an excellent guide for experienced modellers to innovate and improve their methodologies for analysing simulation results.” —Mathematical Reviews

Keywords

Cellular Automata Biological Pattern Formation Adhesive Cell Interaction Cancer Dynamics Tissue Development Pigment Cell Pattern Formation Cell Migration

Authors and affiliations

  • Andreas Deutsch
    • 1
  • Sabine Dormann
    • 2
  1. 1.Centre for Information Services and High Performance ComputingTechnische Universität DresdenDresdenGermany
  2. 2.FB Mathematik/InformatikUniversität OsnabrückOsnabrückGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4899-7980-3
  • Copyright Information Springer Science+Business Media New York 2017
  • Publisher Name Birkhäuser, Boston, MA
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4899-7978-0
  • Online ISBN 978-1-4899-7980-3
  • Series Print ISSN 2164-3679
  • Series Online ISSN 2164-3725
  • Buy this book on publisher's site
Industry Sectors
Pharma