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Biological systems - Computer simulation. --- Biological systems - Mathematical models.

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Biological systems - Mathematical models - Congresses. --- Differential equations - Congresses. --- Differential equations, Nonlinear - Congresses.

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The emerging, multi-disciplinary field of systems biology is devoted to the study of the relationships between various parts of a biological system, and computer modeling plays a vital role in the drive to understand the processes of life from an holistic viewpoint. Advancements in experimental technologies in biology and medicine have generated an enormous amount of biological data on the dependencies and interactions of many different molecular cell processes, fueling the development of numerous computational methods for exploring this data. The mathematical formalism of Petri net theory is able to encompass many of these techniques. This essential text/reference presents a comprehensive overview of cutting-edge research in applications of Petri nets in systems biology, with contributions from an international selection of experts. Those unfamiliar with the field are also provided with a general introduction to systems biology, the foundations of biochemistry, and the basics of Petri net theory. Further chapters address Petri net modeling techniques for building and analyzing biological models, as well as network prediction approaches, before reviewing the applications to networks of different biological classification. Topics and features: Investigates the modular, qualitative modeling of regulatory networks using Petri nets, and examines an Hybrid Functional Petri net simulation case study Contains a glossary of the concepts and notation used in the book, in addition to exercises at the end of each chapter Covers the topological analysis of metabolic and regulatory networks, the analysis of models of signaling networks, and the prediction of network structure Provides a biological case study on the conversion of logical networks into Petri nets Discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques Includes a Foreword by Professor Jens Reich, Professor of Bioinformatics at Humboldt University and Max Delbrück Center for Molecular Medicine in Berlin This unique guide to the modeling of biochemical systems using Petri net concepts will be of real utility to researchers and students of computational biology, systems biology, bioinformatics, computer science, and biochemistry. Dr. Ina Koch is a Professor and holds the Chair of Bioinformatics at the Johann Wolfgang Goethe-University Frankfurt am Main, Germany. Dr. Wolfgang Reisig is a Professor and holds the Chair in the Theory of Programming at the Humboldt University of Berlin, Germany. Dr. Falk Schreiber is a Professor and holds the Chair of Bioinformatics at the Martin Luther University Halle-Wittenberg, Germany, and the Coordinator of Bioinformatics at the Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben, Germany.

Bioinformatics. --- Biological systems -- Computer simulation. --- Biological systems -- Mathematical models. --- Computational biology. --- Systems biology. --- Systems biology --- Petri nets --- Biology --- Health & Biological Sciences --- Biology - General --- Petri nets. --- Computer science. --- Computer Science. --- Computational Biology/Bioinformatics. --- Systems Biology. --- Computational biology --- Bioinformatics --- Biological systems --- Molecular biology --- Bio-informatics --- Biological informatics --- Information science --- Informatics --- Science --- Data processing --- Graph theory --- Nets (Mathematics) --- Biological models. --- Models, Biological

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Mathematical modeling in the biological sciences is growing exponentially because the general area provides exciting problems from biology to medicine, and this goes under the name mathematical biology. Moreover, models of the growth of microorganisms have become very popular since mathematical predictions can be tested in the laboratory employing a device known as the chemostat. Such models are called chemostat models. This book attempts to present a self contained account of mathematical model building theory of microbial populations. Key Features: Covers all fundamental concepts and mathematical skills needed to build models for microbial populations. Provides an accessible and informative over view of known literature including several practical techniques. Presents a comprehensive analysis of chemostat models and their limitations in adapting to natural lakes. A thorough discussion on the design of biologically viable control mechanisms (termed bio-control mechanisms) to contain the instability tendencies. Construction of a variety of Lyapunov functionals for global stability analysis. This book is ideal for a general scientific and engineering audience requiring an in-depth exposure to current ideas, methods and models. The topics discussed can serve as a one to two semester course material for senior under graduate and graduate students. It is a useful reference for practitioners, researchers, and professionals in applied mathematics, biology, agriculture, limnology, chemical and civil engineering.

Biological systems -- Mathematical models. --- Chemostat. --- Microbial populations -- Mathematical models. --- Microbiological Processes. --- Models, Biological. --- Biological systems --- Microbial populations --- Chemostat --- Epidemiologic Measurements --- Models, Theoretical --- Investigative Techniques --- Microbiological Phenomena --- Statistics as Topic --- Phenomena and Processes --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Public Health --- Epidemiologic Methods --- Environment and Public Health --- Health Care --- Biometry --- Microbiological Processes --- Models, Biological --- Methods --- Biology --- Health & Biological Sciences --- Biology - General --- Mathematical models --- Biomathematics. --- Computational biology. --- Mathematics --- Life sciences. --- Systems biology. --- Microbial ecology. --- Community ecology, Biotic. --- Ecology. --- Life Sciences. --- Systems Biology. --- Mathematical and Computational Biology. --- Theoretical Ecology/Statistics. --- Community & Population Ecology. --- Microbial Ecology. --- Bioinformatics --- Biological models. --- Balance of nature --- Bionomics --- Ecological processes --- Ecological science --- Ecological sciences --- Environment --- Environmental biology --- Oecology --- Environmental sciences --- Population biology --- Environmental microbiology --- Microorganisms --- Ecology --- Microbiology --- Ecology . --- Biocenoses --- Biocoenoses --- Biogeoecology --- Biological communities --- Biomes --- Biotic community ecology --- Communities, Biotic --- Community ecology, Biotic --- Ecological communities --- Ecosystems --- Natural communities --- Computational biology --- Molecular biology --- Biological systems - Mathematical models --- Microbial populations - Mathematical models

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Chaotic behavior in systems --- Fractals --- Physiology --- Biological systems --- Mathematical models --- -Chaotic behavior in systems --- -Animal physiology --- Animals --- Biology --- Anatomy --- Fractal geometry --- Fractal sets --- Geometry, Fractal --- Sets, Fractal --- Sets of fractional dimension --- Dimension theory (Topology) --- Chaos in systems --- Chaos theory --- Chaotic motion in systems --- Differentiable dynamical systems --- Dynamics --- Nonlinear theories --- System theory --- Biosystems --- Systems, Biological --- Systems biology --- Philosophy --- -Mathematical models --- -Fractal geometry --- Animal physiology --- Physiology - Mathematical models --- Biological systems - Mathematical models