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(Ebook) Mathematical Modeling in Systems Biology: An Introduction by Brian P. Ingalls ISBN 9780262018883, 0262018888

  • SKU: EBN-4940128
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Authors:Brian P. Ingalls
Pages:424 pages.
Year:2013
Editon:1
Publisher:The MIT Press
Language:english
File Size:20.48 MB
Format:pdf
ISBNS:9780262018883, 0262018888
Categories: Ebooks

Product desciption

(Ebook) Mathematical Modeling in Systems Biology: An Introduction by Brian P. Ingalls ISBN 9780262018883, 0262018888

Systems techniques are integral to current research in molecular cell biology, and system-level investigations are often accompanied by mathematical models. These models serve as working hypotheses: they help us to understand and predict the behavior of complex systems. This book offers an introduction to mathematical concepts and techniques needed for the construction and interpretation of models in molecular systems biology. It is accessible to upper-level undergraduate or graduate students in life science or engineering who have some familiarity with calculus, and will be a useful reference for researchers at all levels.

The first four chapters cover the basics of mathematical modeling in molecular systems biology. The last four chapters address specific biological domains, treating modeling of metabolic networks, of signal transduction pathways, of gene regulatory networks, and of electrophysiology and neuronal action potentials. Chapters 3--8 end with optional sections that address more specialized modeling topics. Exercises, solvable with pen-and-paper calculations, appear throughout the text to encourage interaction with the mathematical techniques. More involved end-of-chapter problem sets require computational software. Appendixes provide a review of basic concepts of molecular biology, additional mathematical background material, and tutorials for two computational software packages (XPPAUT and MATLAB) that can be used for model simulation and analysis.

An introduction to the mathematical concepts and techniques needed for the construction and analysis of models in molecular systems biology. 
(Reprinted in 2022).

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