Chemical Master Equation for Large Biological Networks
State-space Expansion Methods Using AI
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Beschreibung
This book highlights the theory and practical applications of the chemical master equation (CME) approach for very large biochemical networks, which provides a powerful general framework for model building in a variety of biological networks. The aim of the book is to not only highlight advanced numerical solution methods for the CME, but also reveal their potential by means of practical examples. The case studies presented are mainly from biology; however, the applications from novel methods are discussed comprehensively, underlining the interdisciplinary approach in simulation and the potential of the chemical master equation approach for modelling bionetworks. The book is a valuable guide for researchers, graduate students, and professionals alike.
This book highlights the theory and practical applications of the chemical master equation (CME) approach for very large biochemical networks, which provides a powerful general framework for model building in a variety of biological networks. The aim of the book is to not only highlight advanced numerical solution methods for the CME, but also reveal their potential by means of practical examples. The case studies presented are mainly from biology; however, the applications from novel methods are discussed comprehensively, underlining the interdisciplinary approach in simulation and the potential of the chemical master equation approach for modelling bionetworks. The book is a valuable guide for researchers, graduate students, and professionals alike.
Highlights the theory and applications of the chemical master equation (CME) for very large biochemical networks Discusses the novel method comprehensively, underlining the interdisciplinary approach in simulation of CME Presents case studies to validate the theory with practical applications
Autor*in
Don Kulasiri
Themen in »Chemical Master Equation for Large Biological Networks«
Biochemical networks Markov processes Bayesian methods Artificial intelligence Bionetworks Model building Markov tree Markov graphs Numerical simulations Modeling and integration