This textbook presents solid tools for in silico engineering biology, offering students a step-by-step guide to mastering the smart design of metabolic pathways. The first part explains the Design-Build-Test-Learn-cycle engineering approach to biology, discussing the basic tools to model biological and chemistry-based systems. Using these basic tools, the second part focuses on various computational protocols for metabolic pathway design, from enzyme selection to pathway discovery and enumeration. In the context of industrial biotechnology, the final part helps readers understand the challenges of scaling up and optimisation. By working with the free programming language Scientific Python, this book provides easily accessible tools for studying and learning the principles of modern in silico metabolic pathway design. Intended for advanced undergraduates and master’s students in biotechnology, biomedical engineering, bioinformatics and systems biology students, the introductory sections make it also useful for beginners wanting to learn the basics of scientific coding and find real-world, hands-on examples.
This guide offers practical insights into the metabolic engineering of major cell lines, including E. Coli, Bacillus and Yarrowia Lipolytica, and organisms, including human, animal, and plant).
This book introduces methods of optimizing biochemical systems of biotechnological relevance.
This first volume of the Metabolic Pathway Engineering Handbook provides an overview of metabolic pathway engineering with a look towards the future.
... redox cofactor-dependent intracellular enzyme catalysis is expected to interfere with the energy metabolism of the microbial host, since the same cofactors are involved in both redox biocatalysis and energy metabolism.
The Science and Applications of Synthetic and Systems Biology is organized into sections as a topic-by-topic distillation of the presentations and discussions that took place at the workshop.
This volume outlines key steps associated with the design, building, and testing of synthetic metabolic pathways for optimal cell factory performance and robustness, and illustrates how data-driven learning from these steps can be used for ...
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.
First published in 2002, this book introduces researchers and advanced students in biology and engineering to methods of optimizing biochemical systems of biotechnological relevance.
This book covers recent advances and future trends in yeast synthetic biology, providing readers with an overview of computational and engineering tools, and giving insight on important applications.
Since metabolic engineering was first introduced to define a new engineering sub-discipline [1] its development in yeast has been almost synonymous with metabolic engineering in baker's yeast Saccharomyces cerevisiae.