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Titlebook: Cellular Automaton Modeling of Biological Pattern Formation; Characterization, Ex Andreas Deutsch,Sabine Dormann Textbook 2017Latest editio

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書目名稱Cellular Automaton Modeling of Biological Pattern Formation
副標題Characterization, Ex
編輯Andreas Deutsch,Sabine Dormann
視頻videohttp://file.papertrans.cn/224/223001/223001.mp4
概述An accessible presentation with an interdisciplinary approach to cellular automaton models of biological pattern formation.Includes three new chapters on cell migration, tissue development, and cancer
叢書名稱Modeling and Simulation in Science, Engineering and Technology
圖書封面Titlebook: Cellular Automaton Modeling of Biological Pattern Formation; Characterization, Ex Andreas Deutsch,Sabine Dormann Textbook 2017Latest editio
描述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 f
出版日期Textbook 2017Latest edition
關(guān)鍵詞Cellular Automata; Biological Pattern Formation; Adhesive Cell Interaction; Cancer Dynamics; Tissue Deve
版次2
doihttps://doi.org/10.1007/978-1-4899-7980-3
isbn_ebook978-1-4899-7980-3Series ISSN 2164-3679 Series E-ISSN 2164-3725
issn_series 2164-3679
copyrightSpringer Science+Business Media New York 2017
The information of publication is updating

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https://doi.org/10.1007/978-3-322-87349-1cepts and has even triggered new concepts. In the first part, a historical excursion highlights static and dynamic space-time and corresponding mathematical concepts. Pattern forming principles in biology are introduced in the second part.
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Cellular Automataore, we present strategies to analyze spatio-temporal pattern formation in cellular automaton models. In subsec.?., the so-called mean-field theory is presented as an approximative method to study dynamic properties of cellular automata.
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