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

    £999.99

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      Book details

      Publisher Springer International Publishing AG
      Published 9 October 2017
      ISBN-13 9783319631110
      978-3319631110
      ISBN-10 331963111X
      Also in:
      Computing Algorithms and data structures Science & Nature Life sciences: general issues

      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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