Jorge Gonçalves and Sean Warnick
- Published in print:
- 2009
- Published Online:
- August 2013
- ISBN:
- 9780262013345
- eISBN:
- 9780262258906
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262013345.003.0013
- Subject:
- Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies
This chapter introduces the biochemical network, highlighting its role in managing the complexity of biochemical systems and its link to system dynamics. It describes network reconstruction and its ...
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This chapter introduces the biochemical network, highlighting its role in managing the complexity of biochemical systems and its link to system dynamics. It describes network reconstruction and its fundamental difficulties and limitations and the effect of noise and nonlinearities in a biochemical system. It addresses how network reconstruction can be attained using two common types of experiments based on gene silencing and overexpression, and discusses trade-offs between steady-state and time-series data. This chapter shows that the use of dynamic structure functions revealed the dynamic properties of structurally perturbed systems, enabling convenient analysis of modified structures.Less
This chapter introduces the biochemical network, highlighting its role in managing the complexity of biochemical systems and its link to system dynamics. It describes network reconstruction and its fundamental difficulties and limitations and the effect of noise and nonlinearities in a biochemical system. It addresses how network reconstruction can be attained using two common types of experiments based on gene silencing and overexpression, and discusses trade-offs between steady-state and time-series data. This chapter shows that the use of dynamic structure functions revealed the dynamic properties of structurally perturbed systems, enabling convenient analysis of modified structures.
Pablo A. Iglesias and Brian P. Ingalls (eds)
- Published in print:
- 2009
- Published Online:
- August 2013
- ISBN:
- 9780262013345
- eISBN:
- 9780262258906
- Item type:
- book
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262013345.001.0001
- Subject:
- Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies
Issues of regulation and control are central to the study of biological and biochemical systems. Thus it is not surprising that the tools of feedback control theory—engineering techniques developed ...
More
Issues of regulation and control are central to the study of biological and biochemical systems. Thus it is not surprising that the tools of feedback control theory—engineering techniques developed to design and analyze self-regulating systems—have proven useful in the study of these biological mechanisms. Such interdisciplinary work requires knowledge of the results, tools, and techniques of another discipline, as well as an understanding of the culture of an unfamiliar research community. This book attempts to bridge the gap between disciplines by presenting applications of systems and control theory to cell biology that range from surveys of established material to descriptions of new developments in the field. The first chapter offers a primer on concepts from dynamical systems and control theory, which allows the life scientist with no background in control theory to understand the concepts presented in the rest of the book. Following the introduction of ordinary differential equation-based modeling in the first chapter, the second and third chapters discuss alternative modeling frameworks. The remaining chapters sample a variety of applications, considering such topics as quantitative measures of dynamic behavior, modularity, stoichiometry, robust control techniques, and network identification.Less
Issues of regulation and control are central to the study of biological and biochemical systems. Thus it is not surprising that the tools of feedback control theory—engineering techniques developed to design and analyze self-regulating systems—have proven useful in the study of these biological mechanisms. Such interdisciplinary work requires knowledge of the results, tools, and techniques of another discipline, as well as an understanding of the culture of an unfamiliar research community. This book attempts to bridge the gap between disciplines by presenting applications of systems and control theory to cell biology that range from surveys of established material to descriptions of new developments in the field. The first chapter offers a primer on concepts from dynamical systems and control theory, which allows the life scientist with no background in control theory to understand the concepts presented in the rest of the book. Following the introduction of ordinary differential equation-based modeling in the first chapter, the second and third chapters discuss alternative modeling frameworks. The remaining chapters sample a variety of applications, considering such topics as quantitative measures of dynamic behavior, modularity, stoichiometry, robust control techniques, and network identification.
