Cellular Automaton Modeling of Biological Pattern Formation (eBook)

Characterization, Applications, and Analysis

Andreas Deutsch, Sabine Dormann (Autoren)

eBook Download: PDF

2007 | 2005
XXIII, 331 Seiten
Birkhauser Boston (Verlag)
978-0-8176-4415-4 (ISBN)

Infos

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.

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The recent dramatic advances inbiotechnology have led to an explosion of data in the life sciences at the molecular level as well as more detailed observation and ch- acterization at the cellular and tissue levels. Itis now absolutely clear that one needs a theoretical framework inwhich to place this data to gain from it as much information as possible. Mathematical and computational modelling approaches are the obvious waytodothis. Heeding lessons from the physical sciences, one might expect that all areas in the life sciences would be actively pursuing quantitative methods to c- solidate the vast bodies of data that exist and to integrate rapidly accumulating new information. Remarkably, with a few notable exceptions, quite the contrary situation exists. However, things are now beginning to change and there is the sense that we are at the beginning of an exciting new era of research inwhich the novel problems posed by biologists will challenge the mathematicians and computer scientists, who, in turn, will use their tools to inform the experimentalists, who will verify model predictions. Only through such a tight interaction among disciplines will we have the opportunity to solve many of the major problems in the life sciences. One such problem, central to developmental biology, is the understanding of how various processes interact to produce spatio-temporal patterns in the embryo.

Inhalt

Foreword - Philip K. Maini List of Figures List of Notation Introduction and Outline On the Origin of Patterns Mathematical Modeling of Biological Pattern Formation Cellular Automata Random Movement Growth Processes Adhesive Cell Interaction Alignment and Cellular Swarming Pigment Cell Pattern Formation Tissue and Tumor Development Turing Patterns and Excitable Media Discussion and Outlook Appendix A. Growth Processes: A Mean-Field Equation Appendix B. Turing Patterns Appendix C. Excitable Media: Complete Interaction Rule Appendix D. Isotropy, Lattices, and Tensors References Index

Produkt-Details

• Erscheint lt. Verlag: 26.12.2007
• Reihe/Serie: Modeling and Simulation in Science, Engineering and Technology
• Reihe/Serie: Modeling and Simulation in Science, Engineering and Technology
• Vorwort: Philip K. Maini
• Zusatzinfo: XXIII, 331 p.
• Verlagsort: Boston
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik
• Themenwelt: Naturwissenschaften ► Biologie
• Themenwelt: Technik ► Maschinenbau
• Themenwelt: Technik ► Nachrichtentechnik
• Schlagworte: Biocomputing • Development • Java • Modeling • pattern recognition • Simulation • Simulation and modeling
• ISBN-10: 0-8176-4415-6 / 0817644156
• ISBN-13: 978-0-8176-4415-4 / 9780817644154