Overview
- State-of-art approaches with industrial relevance
- Combines and integrates in silico and experimental strategies Internationally leading author consortium
- Explains tools and techniques
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Table of contents (11 chapters)
Keywords
About this book
Systems Metabolic Engineering is changing the way microbial cell factories are designed and optimized for industrial production.
Integrating systems biology and biotechnology with new concepts from synthetic biology enables the global analysis and engineering of microorganisms and bioprocesses at super efficiency and versatility otherwise not accessible. Without doubt, systems metabolic engineering is a major driver towards bio-based production of chemicals, materials and fuels from renewables and thus one of the core technologies of global green growth. In this book, Christoph Wittmann and Sang-Yup Lee have assembled the world leaders on systems metabolic engineering and cover the full story – from genomes and networks via discovery and design to industrial implementation practises.
This book is a comprehensive resource for students and researchers from academia and industry interested in systems metabolic engineering. It provides us with the fundaments to targeted engineering of microbial cells for sustainable bio-production and stimulates those who are interested to enter this exiting research field.
Editors and Affiliations
Bibliographic Information
Book Title: Systems Metabolic Engineering
Editors: Christoph Wittmann, Sang Yup Lee
DOI: https://doi.org/10.1007/978-94-007-4534-6
Publisher: Springer Dordrecht
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Science+Business Media Dordrecht 2012
Hardcover ISBN: 978-94-007-4533-9Published: 16 June 2012
Softcover ISBN: 978-94-017-8319-4Published: 18 July 2014
eBook ISBN: 978-94-007-4534-6Published: 15 June 2012
Edition Number: 1
Number of Pages: XII, 388
Topics: Gene Expression, Systems Biology, Biotechnology, Microbial Genetics and Genomics, Genetic Engineering, Computational Biology/Bioinformatics