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Modeling Biomolecular Networks in Cells Structures and Dynamics

Chen Luonan Wang, Ruiqi Li Chunguang Se alle
Heftet / 2014 / Engelsk

Produktdetaljer

ISBN
9781447157366
Publisert
2014-11-04
Utgiver
Vendor
Springer London Ltd
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet

Forfatter
Chen Luonan
Wang, Ruiqi
Li Chunguang
Aihara Kazuyuki

Om bidragsyterne

Luonan Chen received his M.E. and Ph.D. degrees in electrical engineering from Tohoku University, Sendai, Japan, in 1988 and 1991, respectively. From 1997, he was a member of the faculty of Osaka Sangyo University, Osaka, Japan, and then became a full Professor in the Department of Electrical Engineering and Electronics. He was also the founding director of Institute of Systems Biology, Shanghai University. Since 2010, he has been a professor at Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. His fields of interest are systems biology, bioinformatics, and nonlinear dynamics. He serves as associate editor or editorial board member for many systems biology related journals, e.g. BMC Systems Biology, IEEE/ACM Trans. on Computational Biology and Bioinformatics, IET Systems Biology, Mathematical Biosciences, International Journal of Systems and Synthetic Biology, and the Journal of Systems Science and Complexity. He also serves as Chair of Technical Committee of Systems Biology at the IEEE SMC Society. 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 signal processing, and machine intelligence. 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.

Modeling Biomolecular Networks in Cells Structures and Dynamics

Chen Luonan Wang, Ruiqi Li Chunguang Se alle
Heftet / 2014 / Engelsk
Chen Luonan Wang, Ruiqi Li Chunguang Se alle
Heftet / 2014 / Engelsk
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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 but 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 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". The book also provides theoretical frameworks and tools with which to analyze the nonlinear dynamical phenomena which arise from the connection of building units in a biomolecular network.
Les mer
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.
Les mer
Dynamical Representations of Molecular Networks.- Deterministic Structures of Biomolecular Networks.- Qualitative Analysis of Deterministic Dynamical Networks.- Stability Analysis of Genetic Networks in Lur’e Form.- Design of Synthetic Switching Networks.- Design of Synthetic Oscillating Networks.- Multicellular Networks and Synchronization.
Les mer
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.
Les mer
Shows the reader how nature has often evolved different more efficient solutions from those produced by traditional human approaches to circuits and systems Gives the reader mathematical tools to produce simplified models of molecular networks and interactions Demonstrates how simple biological systems can be synthesised with controllable properties facilitating their use in novel forms of electronics Includes supplementary material: sn.pub/extras
Les mer

Relaterte produkter

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 but 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 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". The book also provides theoretical frameworks and tools with which to analyze the nonlinear dynamical phenomena which arise from the connection of building units in a biomolecular network.
Les mer
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.
Les mer
Dynamical Representations of Molecular Networks.- Deterministic Structures of Biomolecular Networks.- Qualitative Analysis of Deterministic Dynamical Networks.- Stability Analysis of Genetic Networks in Lur’e Form.- Design of Synthetic Switching Networks.- Design of Synthetic Oscillating Networks.- Multicellular Networks and Synchronization.
Les mer
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.
Les mer
Shows the reader how nature has often evolved different more efficient solutions from those produced by traditional human approaches to circuits and systems Gives the reader mathematical tools to produce simplified models of molecular networks and interactions Demonstrates how simple biological systems can be synthesised with controllable properties facilitating their use in novel forms of electronics Includes supplementary material: sn.pub/extras
Les mer

Produktdetaljer

ISBN
9781447157366
Publisert
2014-11-04
Utgiver
Vendor
Springer London Ltd
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet

Forfatter
Chen Luonan
Wang, Ruiqi
Li Chunguang
Aihara Kazuyuki

Om bidragsyterne

Luonan Chen received his M.E. and Ph.D. degrees in electrical engineering from Tohoku University, Sendai, Japan, in 1988 and 1991, respectively. From 1997, he was a member of the faculty of Osaka Sangyo University, Osaka, Japan, and then became a full Professor in the Department of Electrical Engineering and Electronics. He was also the founding director of Institute of Systems Biology, Shanghai University. Since 2010, he has been a professor at Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. His fields of interest are systems biology, bioinformatics, and nonlinear dynamics. He serves as associate editor or editorial board member for many systems biology related journals, e.g. BMC Systems Biology, IEEE/ACM Trans. on Computational Biology and Bioinformatics, IET Systems Biology, Mathematical Biosciences, International Journal of Systems and Synthetic Biology, and the Journal of Systems Science and Complexity. He also serves as Chair of Technical Committee of Systems Biology at the IEEE SMC Society. 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 signal processing, and machine intelligence. 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.

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