Biomolecular Feedback Systems
Autor Domitilla Del Vecchio, Richard M. Murrayen Limba Engleză Hardback – 3 noi 2014
then describes in detail the control and dynamical systems tools used to analyze these models. These include tools for analyzing stability of equilibria, limit cycles, robustness, and parameter uncertainty. Modeling and analysis techniques are then applied to design examples from both natural
systems and synthetic biomolecular circuits. In addition, this comprehensive book addresses the problem of modular composition of synthetic circuits, the tools for analyzing the extent of modularity, and the design techniques for ensuring modular behavior. It also looks at design trade-offs,
focusing on perturbations due to noise and competition for shared cellular resources.Featuring numerous exercises and illustrations throughout, Biomolecular Feedback Systems is the ideal textbook for advanced undergraduates and graduate students. For researchers, it can also serve as a
self-contained reference on the feedback control techniques that can be applied to biomolecular systems.Provides a user-friendly introduction to essential concepts, tools, and applicationsCovers the most commonly used modeling methodsAddresses the modular design problem for biomolecular systemsUses
design examples from both natural systems and synthetic circuitsSolutions manual (available only to professors at press.princeton.edu)An online illustration package is available to professors at press.princeton.edu
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Specificații
ISBN-13: 9780691161532
ISBN-10: 0691161534
Pagini: 392
Ilustrații: 13 halftones. 113 line illus. 3 tables
Dimensiuni: 185 x 261 x 24 mm
Greutate: 0.78 kg
Editura: Princeton University Press
ISBN-10: 0691161534
Pagini: 392
Ilustrații: 13 halftones. 113 line illus. 3 tables
Dimensiuni: 185 x 261 x 24 mm
Greutate: 0.78 kg
Editura: Princeton University Press
Descriere
Provides an introduction to the principles and tools for modeling, analyzing, and synthesizing biomolecular systems. This book begins with modeling tools such as reaction-rate equations, reduced-order models, stochastic models, and specific models of important core processes.