Overview
- Includes cutting-edge methods and protocols
- Provides step-by-step detail essential for reproducible results
- Contains key notes and implementation advice from the experts
Part of the book series: Methods in Molecular Biology (MIMB, volume 2553)
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About this book
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.
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Keywords
Table of contents (19 protocols)
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Front Matter
Editors and Affiliations
Bibliographic Information
Book Title: Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology
Editors: Kumar Selvarajoo
Series Title: Methods in Molecular Biology
DOI: https://doi.org/10.1007/978-1-0716-2617-7
Publisher: Humana New York, NY
eBook Packages: Springer Protocols
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
Hardcover ISBN: 978-1-0716-2616-0Published: 14 October 2022
Softcover ISBN: 978-1-0716-2619-1Published: 13 October 2022
eBook ISBN: 978-1-0716-2617-7Published: 13 October 2022
Series ISSN: 1064-3745
Series E-ISSN: 1940-6029
Edition Number: 1
Number of Pages: XII, 455
Number of Illustrations: 27 b/w illustrations, 133 illustrations in colour
Topics: Bioinformatics