Carlo Cosentino, PhD, is a lecturer in systems and control engineering in the School of Computer and Biomedical Engineering at Magna Græcia 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.

Klappentext

Filling the need for a text on control theory for systems biologists, this self-contained, easy-to-follow book explains how feedback control concepts can be applied to systems biology. Each chapter introduces key topics and case studies that explore applications in cellular and molecular biology. The authors cover tools and techniques for the analysis of linear and nonlinear systems, negative and positive feedback, robustness analysis methods, techniques for the reverse-engineering of biological interaction networks, and the analysis of stochastic biological control systems. A valuable reference, this text offers a sound starting point for scientists entering this fascinating and rapidly developing field.

Zusammenfassung

Like engineering systems, biological systems must also operate effectively in the presence of internal and external uncertaintysuch 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.

Control Theory for Systems Biologists

The book focuses on the fundamental concepts used to analyze the effects of feedback in biological control systems, rather than the control system design methods that form the core of most control textbooks. In addition, the authors do not assume that readers are familiar with control theory. They focus on "control applications" such as metabolic and gene-regulatory networks rather than aircraft, robots, or engines, and on mathematical models derived from classical reaction kinetics rather than classical mechanics. Another significant feature of the book is that it discusses nonlinear systems, an understanding of which is crucial for systems biologists because of the highly nonlinear nature of

Inhalt

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.