Computational Biology And Machine Learning For Metabolic Engineering And Synthetic Biology

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Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology

This volume provides protocols for computational, statistical, and machine learning methods that are mainly applied to the study of metabolic engineering, synthetic biology, and disease applications. These techniques support the latest progress in cross-disciplinary research that integrates the different scales of biological complexity. The topics covered in this book are geared toward researchers with a background in engineering, computational analytical, and modeling experience and cover a broad range of topics in computational and machine learning approaches. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and practical, Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology is a valuable resource for any researcher or scientist who wants to learn more about the latest computational methods and how they are applied toward the understanding and prediction of complex biology.
Metabolic Pathway Engineering

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.
Systems Biology and Synthetic Biology

The genomic revolution has opened up systematic investigations and engineering designs for various life forms. Systems biology and synthetic biology are emerging as two complementary approaches, which embody the breakthrough in biology and invite application of engineering principles. Systems Biology and Synthetic Biology emphasizes the similarity between biology and engineering at the system level, which is important for applying systems and engineering theories to biology problems. This book demonstrates to students, researchers, and industry that systems biology relies on synthetic biology technologies to study biological systems, while synthetic biology depends on knowledge obtained from systems biology approaches.