This book focuses on a challenging application field of cellular automata: pattern formation in biological systems, such as the growth of microorganisms, dynamics of cellular tissue and tumors, and formation of pigment cell patterns. These phenomena, resulting from complex cellular interactions, cannot be deduced solely from experimental analysis, but can be more easily examined using mathematical models, in particular, cellular automaton models. While there are various books treating cellular automaton modeling, this interdisciplinary work is the first one covering biological applications. The book is aimed at researchers, practitioners, and students in applied mathematics, mathematical biology, computational physics, bioengineering, and computer science interested in a cellular automaton approach to biological modeling.

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. QR codes are included within the text for easy access to the simulator. 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

Almost all real systems are nonlinear. For a nonlinear system the superposition principle breaks down: The system's response is not proportional to the stimulus it receives; the whole is more than the sum of its parts. The three parts of this book contains the basics of nonlinear science, with applications in physics. Part I contains an overview of fractals, chaos, solitons, pattern formation, cellular automata and complex systems. In Part II, 14 reviews and essays by pioneers, as well as 10 research articles are reprinted. Part III collects 17 students projects, with computer algorithms for simulation models included.The book can be used for self-study, as a textbook for a one-semester course, or as supplement to other courses in linear or nonlinear systems. The reader should have some knowledge in introductory college physics. No mathematics beyond calculus and no computer literacy are assumed.

The observation of nature has been the inspiration for many materials, laws, and theories, as well as computational methods. Nature-Inspired computing Design, Development, and Applications covers all the main areas of natural computing, from methods to computationally synthesized natural phenomena, to computing paradigms based on natural materials. This volume is comprised of ideas and research from nature to develop computational systems or materials to perform computation. Researchers, academic educators, and professionals will find a comprehensive view of all aspects of natural computing with emphasis on its main branches.

This volume constitutes the thoroughly refereed proceedings of the 21st International Workshop on Cellular Automata and Discrete Complex Systems, AUTOMATA 2015, held in Turku, Finland, in June 2015. This volume contains 4 invited talks in full-paper length and 15 regular papers, which were carefully reviewed and selected from a total of 33 submissions. Topics of interest include, the following aspects and features of such systems: dynamical, topological, ergodic and algebraic aspects; algorithmic and complexity issues; emergent properties; formal language processing aspects; symbolic dynamics; models of parallelism and distributed systems; timing schemes; phenomenological descriptions; scientific modeling; and practical applications.

For four years the Complex Systems Summer School has contributed greatly to education and research into complex systems. 1991 Lectures in Complex Systems presents a wide array of topics in the field, including neural network models for pattern recognition, pattern formation in biological systems, artificial life, ordering condensed matter, fractal time dynamics, cellular automata, complex pattern recognition, and random boolean networks. This book is a compilation of many of the lectures and contributions of the 1991 Complex Systems Summer School, and compliments the previous volumes in this series, Lectures in the Sciences of Complexity edited by Daniel Stein, 1989 Lectures in Complex Systems edited by Erica Jen, and 1990 Lectures in Complex Systems edited by Lynn Nadel and Daniel Stein.