Guide to Simulation and Modeling for Biosciences
Seiten
2015
|
2nd ed. 2015
Springer London Ltd (Verlag)
978-1-4471-6761-7 (ISBN)
Springer London Ltd (Verlag)
978-1-4471-6761-7 (ISBN)
This accessible text presents a detailed introduction to the use of a wide range of software tools and modeling environments for use in the biosciences, as well as the fundamental mathematical background. describes such useful tools as the Maxima algebra system, the PRISM model checker, and the modeling environments Repast Simphony and Smoldyn;
This accessible text presents a detailed introduction to the use of a wide range of software tools and modeling environments for use in the biosciences, as well as the fundamental mathematical background. The practical constraints presented by each modeling technique are described in detail, enabling the researcher to determine which software package would be most useful for a particular problem. Features: introduces a basic array of techniques to formulate models of biological systems, and to solve them; discusses agent-based models, stochastic modeling techniques, differential equations, spatial simulations, and Gillespie’s stochastic simulation algorithm; provides exercises; describes such useful tools as the Maxima algebra system, the PRISM model checker, and the modeling environments Repast Simphony and Smoldyn; contains appendices on rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts; offers supplementary material at an associated website.
This accessible text presents a detailed introduction to the use of a wide range of software tools and modeling environments for use in the biosciences, as well as the fundamental mathematical background. The practical constraints presented by each modeling technique are described in detail, enabling the researcher to determine which software package would be most useful for a particular problem. Features: introduces a basic array of techniques to formulate models of biological systems, and to solve them; discusses agent-based models, stochastic modeling techniques, differential equations, spatial simulations, and Gillespie’s stochastic simulation algorithm; provides exercises; describes such useful tools as the Maxima algebra system, the PRISM model checker, and the modeling environments Repast Simphony and Smoldyn; contains appendices on rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts; offers supplementary material at an associated website.
David J. Barnes is a senior lecturer in computer science at the University of Kent, UK, with a strong background in the teaching of programming and the implementation of computational models of biological systems. Dominique Chu is a senior lecturer in computer science at the University of Kent, UK. He is an expert in mathematical and computational modeling of biological systems, with years of experience in these fields.
Foundations of Modeling.- Agent-based Modeling.- ABMs using Repast Simphony.- Differential Equations.- Mathematical Tools.- Other Stochastic Methods and Prism.- Simulating Biochemical Systems.- Biochemical Models Beyond the Perfect Mixing Assumption.- Reference Material.
| Reihe/Serie | Simulation Foundations, Methods and Applications |
|---|---|
| Zusatzinfo | 80 Illustrations, black and white; XII, 339 p. 80 illus. |
| Verlagsort | England |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Mathematik / Informatik ► Mathematik ► Algebra | |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Naturwissenschaften ► Biologie | |
| Schlagworte | agent-based modeling • algorithms • Bio-Modeling • Computational Biology • Computer Algebra • Differential Equation Models • linear optimization • markov chains • Model |
| ISBN-10 | 1-4471-6761-9 / 1447167619 |
| ISBN-13 | 978-1-4471-6761-7 / 9781447167617 |
| Zustand | Neuware |
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