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This two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout both works are mathematical and computational approaches to examine central problems in the life sciences, ranging from the organizational principles of individual cells to the dynamics of large populations. Volume I covers a number of areas, including: * Cellular Biophysics * Regulatory Networks * Developmental Biology * Biomedical Applications * Data Analysis and Model Validation Volume II examines a diverse range of subjects, including: * Epidemiology * Evolution and Ecology * Immunology * Neural Systems and the Brain * Innovative Mathematical Methods and Education Both volumes will be excellent reference texts for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.

Biological models. --- Biology --- Mathematical models. --- Biological models --- Biomathematics --- Models, Biological --- Bioinformatics. --- Immunology. --- Epidemiology. --- Mathematics. --- Mathematical and Computational Biology. --- Mathematical Modeling and Industrial Mathematics. --- Computational Biology/Bioinformatics. --- Applications of Mathematics. --- Math --- Science --- Diseases --- Public health --- Immunobiology --- Life sciences --- Serology --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Data processing --- Biomathematics. --- Applied mathematics. --- Engineering mathematics. --- Models, Mathematical --- Simulation methods --- Mathematics --- Engineering --- Engineering analysis --- Mathematical analysis

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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 divided into three parts: Part I deals with general principles, theories, and models of pattern formation; Part II examines cellular automaton modeling; and Part III explains various applications. The models and analytic techniques described may be extended to other exciting applications in biology, medicine, and immunology. Key topics and features: * Provides an introduction and historical account of the principles of biological pattern formation (morphogenesis) * Gives an overview of mathematical modeling approaches to morphogenesis, and an introduction to cellular automata and analytic techniques * A supplementary web-based Java applet---Cellular Automaton Simulator---enables interactive simulation of various cellular automaton applications described in the book; available on the internet at www.biomodeling.info * Self-contained presentation is accessible to a broad audience; only basic calculus and linear algebra are required * Careful balance of theory, models, and applications useful to both experimentalists and theoreticians * Includes suggestions for further research topics 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. The book's accessible presentation and interdisciplinary approach make it suitable for graduate and advanced undergraduate courses and seminars in mathematical biology, biomodeling, and biocomputing.

Pattern formation (Biology) --- Cellular automata --- Formation des modèles (Biologie) --- Automates cellulaires --- Mathematical models. --- Modèles mathématiques --- Pattern formation (Biology). --- Biology --- Health & Biological Sciences --- Biophysics --- Biology - General --- Mathematical models --- 576 --- Cellular and subcellular biology. Cytology --- 576 Cellular and subcellular biology. Cytology --- Computers, Iterative circuit --- Iterative circuit computers --- Structures, Tessellation (Automata) --- Tessellation structures (Automata) --- Biological pattern formation --- Life sciences. --- Computer simulation. --- Applied mathematics. --- Engineering mathematics. --- Biomathematics. --- Life Sciences. --- Life Sciences, general. --- Mathematical and Computational Biology. --- Mathematical Modeling and Industrial Mathematics. --- Physiological, Cellular and Medical Topics. --- Applications of Mathematics. --- Simulation and Modeling. --- Developmental biology --- Parallel processing (Electronic computers) --- Pattern recognition systems --- Sequential machine theory --- Physiology --- Mathematics. --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Simulation methods --- Model-integrated computing --- Math --- Science --- Animal physiology --- Animals --- Anatomy --- Biosciences --- Sciences, Life --- Basic Sciences. Mathematics -- Mathematical Models, Simulation Models --- ALLW. --- Models, Mathematical --- Mathematics --- Engineering --- Engineering analysis --- Mathematical analysis

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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.

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