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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.
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.
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.
