Computational Analysis of Biochemical Systems
A Practical Guide for Biochemists and Molecular Biologists
By (author) Eberhard O. Voit
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Computational Analysis of Biochemical Systems by Eberhard O. Voit
Book DescriptionThroughout the foreseeable future, research in medicine, molecular biology, and biotechnology will be dominated by scientific advances resulting from the Human Genome Project. Knowledge of genomes will elucidate disease patterns and promise improved and personalized treatments. Food and drug development will be revolutionized by focused manipulation of genes and biochemical processes. Researchers will begin to construct metabolic pathways from scratch. A true understanding of genetic and metabolic function and design will depend on mathematical and computational methods for analyzing biochemical systems. It will require new ways of thinking and novel approaches of integrative analysis. This book teaches biochemists and molecular biologists the use of modern computational methods for the analysis of complex biomedical systems without assuming more than a modest background in mathematics. The book begins with representations of biochemical systems, provides guidelines for setting up models, discusses in detail mathematical and computational methods of parameter estimation and model analysis, and ultimately connects to the modern literature with four detailed case studies. Every step is illustrated with examples and explored with accompanying software.
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Book DetailsISBN: 9780521780872
(253mm x 203mm x 30mm)
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 4-Sep-2000
Country of Publication: United Kingdom
Books By Author Eberhard O. Voit
Inner Workings of Life, Paperback (May 2016)
An easy-to-read introductory text, comprised of concise vignettes that explain key concepts within systems biology without using jargon.
Pathway Analysis and Optimization in Metabolic Engineering, Paperback (March 2011)» View all books by Eberhard O. Voit
This book introduces researchers and advanced students in biology and engineering to methods of optimizing biochemical systems of biotechnological relevance.
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