Biomolecular Feedback Systems
Domitilla Del Vecchio and Richard M. Murray
Abstract
This book provides an accessible introduction to the principles and tools for modeling, analyzing, and synthesizing biomolecular systems. It begins with modeling tools such as reaction-rate equations, reduced-order models, stochastic models, and specific models of important core processes. It 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 ... More
This book provides an accessible introduction to the principles and tools for modeling, analyzing, and synthesizing biomolecular systems. It begins with modeling tools such as reaction-rate equations, reduced-order models, stochastic models, and specific models of important core processes. It 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, the 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, the book 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.
Keywords:
biomolecular systems,
reaction-rate equation,
stochastic models,
equilibria,
limit cycles,
robustness,
parameter uncertainty
Bibliographic Information
Print publication date: 2014 |
Print ISBN-13: 9780691161532 |
Published to Princeton Scholarship Online: October 2017 |
DOI:10.23943/princeton/9780691161532.001.0001 |
Authors
Affiliations are at time of print publication.
Domitilla Del Vecchio, author
Massachusetts Institute of Technology
Richard M. Murray, author
Caltech
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