A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System Characterizations (eBook)
XVIII, 332 Seiten
Springer Netherland (Verlag)
978-94-017-9041-3 (ISBN)
The complexity of biological systems has intrigued scientists from many disciplines and has given birth to the highly influential field of systems biology wherein a wide array of mathematical techniques, such as flux balance analysis, and technology platforms, such as next generation sequencing, is used to understand, elucidate, and predict the functions of complex biological systems. More recently, the field of synthetic biology, i.e., de novo engineering of biological systems, has emerged. Scientists from various fields are focusing on how to render this engineering process more predictable, reliable, scalable, affordable, and easy.
Systems and control theory is a branch of engineering and applied sciences that rigorously deals with the complexities and uncertainties of interconnected systems with the objective of characterising fundamental systemic properties such as stability, robustness, communication capacity, and other performance metrics. Systems and control theory also strives to offer concepts and methods that facilitate the design of systems with rigorous guarantees on these properties. Over the last 100 years, it has made stellar theoretical and technological contributions in diverse fields such as aerospace, telecommunication, storage, automotive, power systems, and others. Can it have, or evolve to have, a similar impact in biology? The chapters in this book demonstrate that, indeed, systems and control theoretic concepts and techniques can have a significant impact in systems and synthetic biology.
Volume I provides a panoramic view that illustrates the potential of such mathematical methods in systems and synthetic biology. Recent advances in systems and synthetic biology have clearly demonstrated the benefits of a rigorous and systematic approach rooted in the principles of systems and control theory - not only does it lead to exciting insights and discoveries but it also reduces the inordinately lengthy trial-and-error process of wet-lab experimentation, thereby facilitating significant savings in human and financial resources. In Volume I, some of the leading researchers in the field of systems and synthetic biology demonstrate how systems and control theoretic concepts and techniques can be useful, or should evolve to be useful, in order to understand how biological systems function.
As the eminent computer scientist Donald Knuth put it, 'biology easily has 500 years of exciting problems to work on'. This edited book presents but a small fraction of those for the benefit of (1) systems and control theorists interested in molecular and cellular biology and (2) biologists interested in rigorous modelling, analysis and control of biological systems.
The complexity of biological systems has intrigued scientists from many disciplines and has given birth to the highly influential field of systems biology wherein a wide array of mathematical techniques, such as flux balance analysis, and technology platforms, such as next generation sequencing, is used to understand, elucidate, and predict the functions of complex biological systems. More recently, the field of synthetic biology, i.e., de novo engineering of biological systems, has emerged. Scientists from various fields are focusing on how to render this engineering process more predictable, reliable, scalable, affordable, and easy. Systems and control theory is a branch of engineering and applied sciences that rigorously deals with the complexities and uncertainties of interconnected systems with the objective of characterising fundamental systemic properties such as stability, robustness, communication capacity, and other performance metrics. Systems and control theory also strives to offer concepts and methods that facilitate the design of systems with rigorous guarantees on these properties. Over the last 100 years, it has made stellar theoretical and technological contributions in diverse fields such as aerospace, telecommunication, storage, automotive, power systems, and others. Can it have, or evolve to have, a similar impact in biology? The chapters in this book demonstrate that, indeed, systems and control theoretic concepts and techniques can have a significant impact in systems and synthetic biology. Volume I provides a panoramic view that illustrates the potential of such mathematical methods in systems and synthetic biology. Recent advances in systems and synthetic biology have clearly demonstrated the benefits of a rigorous and systematic approach rooted in the principles of systems and control theory - not only does it lead to exciting insights and discoveries but it also reduces the inordinately lengthy trial-and-error process of wet-lab experimentation, thereby facilitating significant savings in human and financial resources. In Volume I, some of the leading researchers in the field of systems and synthetic biology demonstrate how systems and control theoretic concepts and techniques can be useful, or should evolve to be useful, in order to understand how biological systems function. As the eminent computer scientist Donald Knuth put it, "e;biology easily has 500 years of exciting problems to work on"e;. This edited book presents but a small fraction of those for the benefit of (1) systems and control theorists interested in molecular and cellular biology and (2) biologists interested in rigorous modelling, analysis and control of biological systems.
Preface1 On the Mathematics of the Law of Mass Action AuthorsLeonard Adleman, Manoj Gopalkrishnan, Ming-Deh Huang, Pablo Moisset, and Dustin Reishus2 Structural Analysis of Biological Networks AuthorsFranco Blanchini and Elisa Franco3 Guaranteeing Spatial Uniformity in Reaction-Diffusion Systems Using WeightedL2-norm ContractionsZahra Aminzare, Yusef Shafi, Murat Arcak, and Eduardo D. Sontag4 Robust Tunable Transcriptional Oscillators using Dynamic InversionVishwesh V. Kulkarni, Aditya A. Paranjape, and Soon-Jo Chung5 Towards the Modular Decomposition of the Metabolic NetworkAnne Goelzer and Vincent Fromion6 An Optimal Control Approach to Seizure Detection in Drug-Resistant EpilepsySabato Santaniello, Samuel P. Burns, Christophe C. Jouny, William S. Anderson,Gregory K. Bergey, and Sridevi V. Sarma7 Model Reduction of Genetic-Metabolic Networks via Time-Scale SeparationJuan Kuntz, Diego Oyarz ́un, and Guy-Bart Stan8 Networks, Metrics, and Systems BiologySoumen Roy9 Understanding and Predicting Biological Networks Using Linear System IdentificationAlberto Carignano, Ye Yuan, Neil Dalchau, Alex A. R. Webb, and Jorge Gonc ̧alves10 Model Checking in BiologyJasmin Fisher and Nir Piterman11 Computational Design of Informative Experiments in Systems BiologyAlberto Giovanni Busetto, Mikael Sunn ̊aker and Joachim M. Buhrmann12 Predicting Phenotype from Genotype through Reconstruction and Integrative Modeling of Metabolic and Regulatory NetworksSriram ChandrasekaranIndex
Erscheint lt. Verlag | 3.7.2014 |
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Zusatzinfo | XVIII, 332 p. 84 illus., 41 illus. in color. |
Verlagsort | Dordrecht |
Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Informatik |
Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
Studium ► 1. Studienabschnitt (Vorklinik) ► Biochemie / Molekularbiologie | |
Naturwissenschaften ► Biologie | |
Technik | |
Schlagworte | Computational Biology • Computer Science • Electrical Engineering • Synthetic biology • systems biology |
ISBN-10 | 94-017-9041-8 / 9401790418 |
ISBN-13 | 978-94-017-9041-3 / 9789401790413 |
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