Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology (Hardcover, 1st ed. 2023)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Methods in Molecular Biology, 2553
Release date:	October 2022
First published:	2023
Editors:	Kumar Selvarajoo
Dimensions:	254 x 178mm (L x W)
Format:	Hardcover
Pages:	455
Edition:	1st ed. 2023
ISBN-13:	978-1-07-162616-0
Categories:	Books > Science & Mathematics > Biology, life sciences > Molecular biology
LSN:	1-07-162616-7
Barcode:	9781071626160

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