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Systems Evolutionary Biology Biological Network Evolution Theory, Stochastic Evolutionary Game Strategies, and Applications to Systems Synthetic Biology

Langue : Anglais

Auteur :

Couverture de l’ouvrage Systems Evolutionary Biology

Systems Evolutionary Biology: Biological Network Evolution Theory, Stochastic Evolutionary Game Strategies, and Applications to Systems Synthetic Biology discusses the evolutionary game theory and strategies of nonlinear stochastic biological networks under random genetic variations and environmental disturbances and their application to systematic synthetic biology design. The book provides more realistic stochastic biological system models to mimic the real biological systems in evolutionary process and then introduces network evolvability, stochastic evolutionary game theory and strategy based on nonlinear stochastic networks in evolution. Readers will find remarkable, revolutionary information on genetic evolutionary biology that be applied to economics, engineering and bioscience.

Part I: General Theory of Stochastic Evolutionary Biological Network1. Introduction to Systems Evolutionary Biology2. Stochastic Dynamics Systems and Stochastic Nash Game in Evolutionary Biological Networks3. Evolutionary Gene Regulatory Networks and Biochemical Networks4. Evolutionary Ecological Networks

Part II: Applications of Network Evolution to Systems Synthetic Biology5. Robust Design for Evolutionary Synthetic Gene Networks under Genetic Mutations and Environmental Disturbances: Genetic Algorithm (GA) Approach in Genotype Space6. Robust Design of Genetic Networks: Evolutionary Systems Biology Approach via Evolutionary Algorithm (EA) in Phenotype space7. On the Adaptive Design Rules of Biochemical Networks in Evolution

Part III: Stochastic Evolutionary Game Strategies8. Stochastic Evolutionary Game as Natural Selection in a Population of Biological Networks9. Stochastic Noncooperative and Cooperative Evolutionary Game Strategies of a Population of Biological Networks under Natural Selection10. Evolutionary Game Strategy of Evolutionary Biological Network of Somatic Cells in the Organ Carcinogenesis and Aging Process

Part IV: Evolution Measurements of Biological Networks11. On the System Entropy of Nonlinear Stochastic Biological Networks and Its Relationship to Network Evolution12. On the Evolution Measurement of Somatic Networksby the Changes of their Robustness and Response Ability in the Aging Process via Microarray Data

graduate students and researchers in systems biology, synthetic biology, computational biology, stochastic system and evolutionary optimization computation, evolutionary biology and control system engineering

Bor-Sen Chen received B.S. degree of electrical Engineering from Tatung Institute of Technology in 1970, M.S. degree of Geophysics from National Central University in 1973, and PhD in Electrical Engineering from University of Southern California in 1982. He is an expert on the topic of nonlinear robust control and filter designs based on stochastic Nash game theory to override the influence of intrinsic random fluctuations and attenuate the effect of environmental disturbances, which can be applied to evolutionary game strategies of biological networks under natural selection to respond to random genetic variations and environmental disturbances in the evolutionary process. Prof. Chen had audited more than 10 courses of biology before his research in systems biology. He has published about 100 papers in bioinformatics and systems biology. Further, he have published more than 100 papers in system theory and control, and more than 80 papers of signal processing and communication. In the last three years, he has also published 7 monographs. He was elected to an IEEE Fellow in 2001 and became an IEEE Life Fellow in 2014.
  • Explains network fitness, network evolvability and network robustness of biological networks from the systematic perspective
  • Discusses the evolutionary noncooperative and cooperative game strategies of biological networks
  • Offers detailed diagrams to help readers understand biological networks, their systematic behaviors and the simulational results of evolutionary biological networks
  • Includes examples in every chapter with computational simulation to illustrate the solution procedure of evolutionary theory, strategy and results

Date de parution :

Ouvrage de 390 p.

19x23.3 cm

Disponible chez l'éditeur (délai d'approvisionnement : 14 jours).

145,45 €

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