A Guide to Numerical Modelling in Systems Biology (Texts in Computational Science and Engineering)

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9783319200583: A Guide to Numerical Modelling in Systems Biology (Texts in Computational Science and Engineering)

This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.

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About the Author:

Peter Deuflhard, founder of ZIB and co-founder of MATHEON in Berlin, has written successful books in numerical analysis and scientific computing (three of them with Springer).

Susanna Röblitz is Head of the research group Computational Systems Biology at ZIB and professor for Applied Mathematics and Bioinformatics at FU Berlin.

 

Review:

“This book is structured in three chapters covering the ODE modeling for the identification and characterization of biological networks, the handling of numerical simulations for the proposed ODE models and the corresponding parameters identification, respectively. ... included a list of numerical algorithms and software packages that facilitate the understanding of the ODE-related problems. ... written in an accessible manner, with plenty of examples, making it a valuable addition to the series of textbooks in computational science and engineering.” (Irina Ioana Mohorianu, zbMATH, Vol. 1325.92001, 2016)

“It focuses almost solely on the mundane mathematical topic of ordinary differential equations (ODEs) and their parameter estimation ... . the prime readership for this volume is to be found more amongst advanced researchers in systems biology trying to find reasons for unstable results of some ODE simulation or identification packages.” (L.-F. Pau, Computing Reviews, November, 2015)

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