Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology

Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology

Author: Kumar Selvarajoo

Publisher: Springer Nature

Published: 2022-10-13

Total Pages: 457

ISBN-13: 1071626175

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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.


Systems and Synthetic Metabolic Engineering

Systems and Synthetic Metabolic Engineering

Author: Yanfeng Liu

Publisher: Academic Press

Published: 2020-07-10

Total Pages: 294

ISBN-13: 0128217529

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Systems and Synthetic Metabolic Engineering provides an overview of the development of metabolic engineering within medicine that is fueled by systems and synthetic biology. These newly developed, successful strategies of metabolic engineering guide the audience on how to propose and test proper strategies for metabolic engineering research. In addition to introductory, regulatory and challenges in the field, the book also covers dynamic control and autonomous regulation to control cell metabolism, along with computational modeling and industrial applications. The book is written by leaders in the field, making it ideal for synthetic biologists, researchers, students and anyone working in this area. Discusses the current progress of metabolic engineering, focusing on systems biology and synthetic biology Covers introductory, regulatory, strategies, production and challenges in the field Written technically for synthetic biologists, researchers, students, industrialists, policymakers and stakeholders


Metabolic Pathway Design

Metabolic Pathway Design

Author: Pablo Carbonell

Publisher: Springer Nature

Published: 2019-11-05

Total Pages: 168

ISBN-13: 3030298655

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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.


Machine Learning and Systems Biology in Genomics and Health

Machine Learning and Systems Biology in Genomics and Health

Author: Shailza Singh

Publisher: Springer Nature

Published: 2022-02-04

Total Pages: 239

ISBN-13: 9811659931

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This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.


Metabolic Pathway Engineering

Metabolic Pathway Engineering

Author: Jean F. Challacombe

Publisher: CRC Press

Published: 2021-07-14

Total Pages: 116

ISBN-13: 1000260542

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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.


Systems Biology

Systems Biology

Author: Bor-Sen Chen

Publisher: Nova Science Publishers

Published: 2014

Total Pages: 0

ISBN-13: 9781633215887

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This text not only describes the current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers but also discusses challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.


Systems Metabolic Engineering

Systems Metabolic Engineering

Author: Christoph Wittmann

Publisher: Springer

Published: 2014-07-18

Total Pages: 0

ISBN-13: 9789401783194

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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.


Artificial Intelligence Methods and Tools for Systems Biology

Artificial Intelligence Methods and Tools for Systems Biology

Author: W. Dubitzky

Publisher: Springer Science & Business Media

Published: 2007-09-29

Total Pages: 231

ISBN-13: 140205811X

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This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain. As design blueprint, the book is intended for scientists and other professionals tasked with developing and using AI technologies in the context of life sciences research. As a user guide, this volume addresses the requirements of researchers to gain a basic understanding of key AI methodologies for life sciences research. Its emphasis is not on an intricate mathematical treatment of the presented AI methodologies. Instead, it aims at providing the users with a clear understanding and practical know-how of the methods. As a research agenda, the book is intended for computer and life science students, teachers, researchers, and managers who want to understand the state of the art of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. Our aim was to maintain the readability and accessibility of a textbook throughout the chapters, rather than compiling a mere reference manual. The book is also intended as a communication platform seeking to bride the cultural and technological gap among key systems biology disciplines. To support this function, contributors have adopted a terminology and approach that appeal to audiences from different backgrounds.


Synthetic Biology-Guided Metabolic Engineering

Synthetic Biology-Guided Metabolic Engineering

Author: Rodrigo Ledesma-Amaro

Publisher: Frontiers Media SA

Published: 2020-05-05

Total Pages: 142

ISBN-13: 2889637085

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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.


Synthetic Biology and iGEM: Techniques, Development and Safety Concerns

Synthetic Biology and iGEM: Techniques, Development and Safety Concerns

Author: Kang Ning

Publisher: Springer Nature

Published: 2023-06-19

Total Pages: 119

ISBN-13: 981992460X

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This book focuses on biological engineering techniques, multi-omics big-data integration, and data-mining techniques, as well as cutting-edge researches in principles and applications of several synthetic biology applications. Synthetic biology is a new research area, while it has been rooted from the long-established area including biological engineering, metabolite engineering, and systems biology. This book will discuss the following aspects: (1) introduction to synthetic biology and iGEM, especially focusing on the systematic design, rational engineering, and sustainability of design in the omics ages; (2) synthetic biology–related multi-omics data integration and data mining techniques; (3) the technical issues, development issues, and safety issues of synthetic biology; (4) data resources, web services, and visualizations for synthetic biology; and (5) advancement in concrete research on synthetic biology, with several case studies shown. Devised as a book on synthetic biology research and education in the omics age, this book has put focuses on systematic design, rational engineering, and sustainability of design for synthetic biology, which will explain in detail and with supportive examples the “What,” “Why,” and “How” of the topic. It is an attempt to bridge the gap between synthetic biology’s research and education side, for best practice of synthetic biology and in-depth insights for the related questions.