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Taylor & Francis Metabolic Pathway Engineering: Analysis and Applications in the Life Sciences

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Metabolic systems engineering combines the tools and approaches of systems biology, synthetic biology, and evolutionary engineering. This book reviews studies on metabolism, from the earliest work of Lavoisier and Buchner to current cutting-edge research in metabolic systems engineering.  This technology has been used in bioengineering applications to create high-performing microbes and plants that produce important chemicals, pharmaceuticals, crops, and other natural products. Current applications include optimizing metabolic pathways to enhance degradation of biomass for biofuel production and accelerated processing of environmental waste products and contaminants. The book includes examples to illustrate the applications of this technology in the optimization of metabolic pathways to create robust industrial strains as well as in the engineering of biological processes involving health and diseases of humans, animals, and plants.  Written by a seasoned computational biologist with many years of experience in genomics, bioinformatics, and systems biology, this book will appeal to anyone interested in metabolic systems analysis and metabolic pathway engineering. About the Author Jean F. Challacombe is senior genomics bioinformatics specialist in the Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, USA. She holds a BS in pharmacology, a PhD in neuroscience, and equivalent education and experience to a MS in computer science. Dr. Challacombe is an expert of next-generation sequence analysis of metagenomes and metatranscriptomes; metabolic pathway analysis and modeling; proteome analysis; algorithm and software development with various machine learning tools; design, implementation and administration of different database systems; UNIX/Linux/Mac system administration; high-performance, parallel and distributed computing; and web application development. She enjoys using computational methods to solve complex biological problems.

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