Simulation Algorithms for Computational Systems Biology / by Luca Marchetti, Corrado Priami, Vo Hong Thanh.

By:

Marchetti, Luca [author.]

Contributor(s):

Material type: Text

TextSeries: Texts in Theoretical Computer Science. An EATCS SeriesPublisher: Cham : Springer International Publishing : Imprint : Springer, 2017Copyright date: [2017]Description: XI, 238 pages : illustrations ; 24 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9783319631134
3319631136

Subject(s):

Genre/Form:

Electronic books.

Additional physical formats: Printed edition:: No titleDDC classification:

005.1 23 M.L.S

LOC classification:

QA76.9.A43

Online resources:

Click here to access online

Contents:

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

Summary: 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.

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Books	Main library A1	Computers & Information Technology ( Computer Science )	005.1 M.L.S (Browse shelf(Opens below))	1	Available		00015716

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Include bibliographical references.

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

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.

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