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Models, Biological --- Receptors, Cell Surface --- Signal Transduction --- Cell receptors --- Cellular signal transduction --- Récepteurs cellulaires --- Transduction du signal cellulaire --- Cell receptors. --- Cellular signal transduction. --- Récepteurs cellulaires --- Models, Biological. --- Receptors, Cell Surface. --- Signal Transduction.
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Systems biology is a critical emerging field that quantifies and annotates the complexity of biological systems in order to construct algorithmic models to predict outcomes from component input. Applications in medicine are revolutionizing our understanding of biological processes and systems.Systems Biomedicine is organized around foundations, computational modeling, network biology, and integrative biology, with the extension of examples from human biology and pharmacology, to focus on the applications of systems approaches to medical problems. An integrative approach to the u
Systems biology. --- Medical sciences --- Computer simulation. --- Basic medical sciences --- Basic sciences, Medical --- Biomedical sciences --- Health sciences --- Preclinical sciences --- Sciences, Medical --- Life sciences --- Medicine --- Computational biology --- Bioinformatics --- Biological systems --- Molecular biology
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Systems biology is a critical emerging field that seeks to define the interactions of all biological components by examining underlying biochemical and genetic processes. It is a discipline that quantifies and annotates the complexity of biological systems in order to construct algorithmic models to predict outcomes from component input. Applications in medicine are revolutionizing our understanding of biological processes and systems. Systems Biomedicine is organized around foundations, computational modelling, network biology, and integrative biology, with the extension of examples from human biology and pharmacology, to focus on the applications of systems approaches to medical problems. An integrative approach to the underlying genomic, proteomic, and computational biology principles provides researchers with guidance in the use of qualitative systems and hypothesis generators. To reflect the highly interdisciplinary nature of the field, careful detail has been extended to ensure explanations of complex mathematical and biological principles are clear with minimum technical jargon.
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Receptors: Models for Binding, Trafficking, and Signaling bridges the gap between chemical engineering and cell biology by lucidly and practically demonstrating how a mathematical modeling approach combined with quantitative experiments can provide enhanced understanding of cell phenomena involving receptor/ligand interactions. In stressing the need for a quantitative understanding of how receptor-mediated cell functions depend on receptor and ligand properties, the book offers comprehensive treatments of both basic and state-of-the-art model frameworks that span the entire spectrum of receptor processes--from fundamental cell surface binding, intracellular trafficking, and signal transduction events to the cell behavioral functions they govern, including proliferation, adhesion, and migration. The book emphasizes mechanistic models that are accessible to experimental testing and includes detailed examples of important contemporary issues. This much-needed book introduces chemical engineers and bioengineers to important problems in receptor biology and familiarizes cell biologists with the insights that can be gained from engineering analysis and synthesis. As such, chemical engineers, researchers, and advanced students in the fields of biotechnology, biomedical sciences, bioengineering, and molecular cell biology will find this book to be conceptually rich, timely, and useful.
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Systems biology is defined for the purpose of this study as the understanding of biological network behaviors, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment. This involves a variety of approaches, such as the identification and validation of networks, the creation of appropriate datasets, the development of tools for data acquisition and software development, and the use of modeling and simulation software in close linkage with experiment. All of these are discussed in this volume. Of course, the definition becomes ambiguous at the margins, but at the core is the focus on networks, which makes it clear that the goal is to understand the operation of the systems, rather than the component parts. It was concluded that the U.S. is currently ahead of the rest of the world in systems biology, largely because of earlier investment by funding organizations and research institutions. This is reflected in a large number of active research groups, and educational programs, and a diverse and growing funding base. However, there is evidence of rapid development outside the U.S., much of it begun in the last two to three years. Overall, however, the picture is of an active field in the early stages of explosive growth. This volume is aimed at academic researchers, government research agency representatives and graduate students.
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