Chemical Master Equation for Large Biological Networks: State-space Expansion Methods Using AI

This book provides a comprehensive guide to the chemical master equation approach for modelling large biochemical networks, with advanced numerical solution methods and practical examples from biology and other interdisciplinary fields. It is a valuable resource for researchers, graduate students, and professionals.

Format: Paperback / softback
Length: 217 pages
Publication date: 13 September 2022
Publisher: Springer Verlag, Singapore

This comprehensive book delves into the theory and practical applications of the chemical master equation (CME) approach, offering a powerful framework for modeling large biochemical networks. Its primary objective is to showcase advanced numerical solution methods for the CME while demonstrating their potential through practical examples. The case studies presented primarily originate from the realm of biology, highlighting the interdisciplinary nature of simulation and the immense potential of the CME approach in capturing the complexity of bionetworks. Whether you are a researcher, graduate student, or professional, this book serves as a valuable resource, providing insights and guidance into the realm of biochemical network modeling.

The chemical master equation (CME) approach is a powerful tool for modeling large biochemical networks. It provides a framework for understanding the dynamics of these complex systems and allows for the simulation of their behavior. The book focuses on the theory and practical applications of the CME approach, highlighting advanced numerical solution methods and their potential through practical examples.

The case studies presented in the book are primarily from the realm of biology, showcasing the interdisciplinary nature of simulation and the potential of the CME approach in capturing the complexity of bionetworks. These case studies cover a range of topics, including drug discovery, gene expression, and metabolic pathways.

One of the key strengths of the CME approach is its ability to handle the dynamics of a large number of species and reactions. This makes it suitable for modeling complex biological systems, such as the human body or a community of microorganisms. The book discusses various numerical solution methods for the CME, including finite difference, finite element, and stochastic differential equations. These methods are used to solve the equations that describe the dynamics of the biochemical network.

In addition to discussing numerical solution methods, the book also highlights the potential of the CME approach for modeling bionetworks. Bionetworks are complex systems that consist of multiple interacting species, and the CME approach provides a powerful tool for understanding their behavior. The book discusses various applications of the CME approach in modeling bionetworks, including drug discovery, disease modeling, and ecological systems.

Overall, this book is a valuable resource for researchers, graduate students, and professionals interested in modeling large biochemical networks. It provides a comprehensive overview of the theory and practical applications of the CME approach, highlighting advanced numerical solution methods and their potential through practical examples. Whether you are working on drug discovery, disease modeling, or ecological systems, this book will provide you with insights and guidance into the realm of biochemical network modeling.

Weight: 367g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811653537
Edition number: 1st ed. 2021