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Modelling Metabolism with Mathematica
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Modelling Metabolism with Mathematica

Book Details

Format Paperback / Softback
ISBN-10 0367395223
ISBN-13 9780367395223
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date Oct 23rd, 2019
Print length 328 Pages
Weight 476 grams
Product Classification: Medicine: general issues
Ksh 12,250.00
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Using the human erythrocyte as an example, this book presents the approaches, methods, tools, and algorithms for modelling the chemical-dynamics of metabolic pathways. The authors explain the concepts underpinning the deterministic theory of chemical and enzyme kinetics in such a way that readers will be able to formulate their own models of time-dependent metabolic systems. They present a graded series of computer models of metabolic pathways leading up to that of human erythrocyte metabolism, and they document a consistent set of rate equations and associated kinetic parameters relevant to the human erythrocyte, which makes the book of particular interest to readers involved with red cell enzymology.
With the advent of sophisticated general programming environments like Mathematica, the task of developing new models of metabolism and visualizing their responses has become accessible to students of biochemistry and the life sciences in general. Modelling Metabolism with Mathematica presents the approaches, methods, tools, and algorithms for modelling the chemical-dynamics of metabolic pathways. The authors explain the concepts underpinning the deterministic theory of chemical and enzyme kinetics, present a graded series of computer models of metabolic pathways leading up to that of the human erythrocyte, and document a consistent set of rate equations and associated kinetic parameters.

The experimental and theoretical study of metabolism in mammalian cells has a long and fruitful history, but our understanding of cellular metabolism at the molecular level is far from complete. This book enables its readers to formulate their own models of time-dependent metabolic systems and aids them in the quest for the many fundamental and clinically relevant discoveries that remain to be made.

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