Modeling Biomolecular Networks in Cells (PDF)
Taking ideas from nature has been a theme of humanity's technological progress but it is only our newfound expertise in molecular manipulation and complex nonlinear dynamics that allows us the prospect of conscripting the building blocks of life as a...
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Taking ideas from nature has been a theme of humanity's technological progress but it is only our newfound expertise in molecular manipulation and complex nonlinear dynamics that allows us the prospect of conscripting the building blocks of life as a means of furthering our abilities in circuits, systems and computers by the control of cellular networks.
Modeling Biomolecular Networks in Cells shows how the interaction between the molecular components of basic living organisms can be modelled mathematically and the models used to create artificial biological entities within cells. Such forward engineering is a difficult task because of the ill-posed nature of the problems and because of the fundamental complexity of the interactions within even the most primitive biological cell. The nonlinear dynamical methods espoused in this book simplify the biology so that it can be successfully understood and the synthesis of simple biological oscillators and rhythm-generators made feasible. Such simple but, from an engineering point of view, unconventional units can then be co-ordinated using intercellular signal biomolecules. The formation of such man-made multicellular networks with a view to the production of biosensors, logic gates, new forms of integrated circuitry based on "gene-chips" and even biological computers is an important step in the design of faster and more flexible "electronics" for the future. The book also provides theoretical frameworks and tools with which to analyze the nonlinear dynamical phenomena, such as collective behaviour, which arise from the connection of building blocks in a biomolecular network.
Researchers and graduate students from a variety of disciplines: engineering, applied mathematics, computer science and quantitative biology will find this book instructive and valuable. The text assumes a basic understanding of differential equations and the necessary molecular biology is dealt with chapter by chapter soonly high-school biology is required.
Ruiqi Wang received an M.S. degree in mathematics from Yunnan University, Kunming, China, in 1999, and a Ph. D. degree in mathematics from the Academy of Mathematics and Systems Science, CAS, Beijing, China, in 2002.
Since 2007, he has been a member of the faculty of Shanghai University, Shanghai, China, where he is currently an Associate Professor at Institute of Systems Biology. His fields of interest are systems biology and nonlinear dynamics.
Chunguang Li received an M.S. degree in Pattern Recognition and Intelligent Systems and a Ph.D. degree in Circuits and Systems from the University of Electronic Science and Technology of China, Chengdu, China, in 2002 and 2004, respectively. Currently, he is a Professor
with the Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China. His current research interests include computational neuroscience, statistical
Kazuyuki Aihara received a B.E. degree of electrical engineering in 1977 and a Ph.D. degree of electronic engineering 1982 from the University of Tokyo, Japan. Currently, he is Professor of the Institute of Industrial Science, Professor of the Graduate School of Information Science and Technology, and Director of Collaborative Research Center for Innovative Mathematical Modelling at the University of Tokyo. His research interests include mathematical modeling of complex systems, parallel distributed processing with spatio-temporal chaos, and time series analysis of complex data.
- Autoren: Luonan Chen , Ruiqi Wang , Chunguang Li , Kazuyuki Aihara
- 2010, 2010, 343 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 1849962146
- ISBN-13: 9781849962148
- Erscheinungsdatum: 05.07.2010
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- Dateiformat: PDF
- Größe: 8.51 MB
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