Description

Book Synopsis

This book explains the state-of-the-art algorithms used to simulate biological dynamics. Each technique is theoretically introduced and applied to a set of modeling cases. Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies.

This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics. An appendix covers the mathematical background, and the authors include further reading sections in each chapter.



Trade Review
“I will not hesitate to recommend … this book, both as an introductory explanation as well as later on when they are deep in a modeling exercise and need to understand the many subtle yet important variations of stochastic simulation techniques applicable to biological systems.” (Sara Kalvala, Computing Reviews, March, 2018)​

Table of Contents
Introduction.- Deterministic Simulation Algorithms.- Stochastic Simulation Algorithms.- Hybrid Simulation Algorithms.- Reaction-Diffusion Systems.- Conclusions and Perspectives.

Simulation Algorithms for Computational Systems

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Order before 4pm today for delivery by Tue 13 Jan 2026.

A Hardback by Luca Marchetti, Corrado Priami, Vo Hong Thanh

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    View other formats and editions of Simulation Algorithms for Computational Systems by Luca Marchetti

    Publisher: Springer International Publishing AG
    Publication Date: 09/10/2017
    ISBN13: 9783319631110, 978-3319631110
    ISBN10: 331963111X

    Description

    Book Synopsis

    This book explains the state-of-the-art algorithms used to simulate biological dynamics. Each technique is theoretically introduced and applied to a set of modeling cases. Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies.

    This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics. An appendix covers the mathematical background, and the authors include further reading sections in each chapter.



    Trade Review
    “I will not hesitate to recommend … this book, both as an introductory explanation as well as later on when they are deep in a modeling exercise and need to understand the many subtle yet important variations of stochastic simulation techniques applicable to biological systems.” (Sara Kalvala, Computing Reviews, March, 2018)​

    Table of Contents
    Introduction.- Deterministic Simulation Algorithms.- Stochastic Simulation Algorithms.- Hybrid Simulation Algorithms.- Reaction-Diffusion Systems.- Conclusions and Perspectives.

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