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Like engineering systems, biological systems must also operate effectively in the presence of internal and external uncertainty--such as genetic mutations or temperature changes, for example. It is not surprising, then, that evolution has resulted in the widespread use of feedback, and research in systems biology over the past decade has shown that feedback control systems are widely found in biology. As an increasing number of researchers in the life sciences become interested in control-theoretic ideas such as feedback, stability, noise and disturbance attenuation, and robustness, there is a need for a text that explains feedback control as it applies to biological systems.
Written by established researchers in both control engineering and systems biology, "Feedback Control in Systems Biology" explains how feedback control concepts can be applied to systems biology. Filling the need for a text on control theory for systems biologists, it provides an overview of relevant ideas and methods from control engineering and illustrates their application to the analysis of biological systems with case studies in cellular and molecular biology.
- Introduction
- Linear systems
- Nonlinear systems
- Negative feedback systems
- Positive feedback systems
- Model validation using robustness analysis
- Reverse engineering biomolecular networks
- Stochastic effects in biological control systems
Index
Carlo Cosentino, PhD, is a lecturer in systems and control engineering in the School of Computer and Biomedical Engineering at Magna Gracia University of Catanzaro, Italy, where he has taught courses in the area of control engineering as well as a course on modeling of biological systems. He has authored more than 60 scientific publications in the fields of control engineering and systems biology, which have appeared in peer reviewed journals and international conferences. His current research interests are in the field of systems and control theory, with particular emphasis on its application to the investigation of biological systems at the cellular and molecular levels.
Declan Bates, PhD, is a professor of biological systems engineering in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, UK. He has authored more than 90 technical publications and is currently Vice-Chair of the Research Grants Review Committee of the International Human Frontier Science Program and a member of the editorial board of IET Systems Biology. His research is focused on the development and application of advanced control system design and analysis methods for aerospace and systems biology applications.
... sets out the powerful engineering perspective on biological systems in all of its glory. Comprehensive, thoughtful and accessible, this is one of the best books in the field.
- Prof. Michael Stumpf, Division of Molecular Biosciences, Imperial College London
"This is an excellent book which will be enjoyed by biologists and theoreticians alike. The authors skilfully combine key concepts from control theory with real cases studies in order to show how the theory can be used both to study and to gain insight into biological networks."
- Prof. Helen Byrne, Centre for Collaborative Applied Mathematics, University of Oxford
"Cosentino and Bates address one of the great educational challenges for systems biology--namely the inaccessibility of control theory to life scientists. As so many researchers have demonstrated, control theory has profound relevance for the study of biophysical systems, but Cosentino and Bates are the first to address this topic in a self contained manner for the uninitiated. This book is an essential resource for life scientists interested in the principles of feedback control and nonlinear dynamics."
- Prof. Frank Doyle, Department of Chemical Engineering, University of California at Santa Barbara
"Systems biology is an inherently interdisciplinary endeavor, and Cosentino and Bates seamlessly interweave these perspectives into an engaging and comprehensive text that is equally accessible to biologists, computational scientists, and engineers. Through their detailed examination of case studies, the authors develop a general conceptual framework for using quantitative analysis to better understand biological systems. This book is an excellent introduction for researchers new to the field, and it provides compelling and contemporary content for engineering courses on dynamics and control."
- Prof. Joshua Leonard, Department of Chemical and Biological Engineering, Northwestern University
