Selvarajoo Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology

Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology

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Beschreibung

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 SyntheticBiology 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. 

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. 



Includes cutting-edge methods and protocols Provides step-by-step detail essential for reproducible results Contains key notes and implementation advice from the experts

Autor*in

Kumar Selvarajoo

Themen in »Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology«

Recombinase Logic Gate Circuits Design Proteomics Transcription Factors high-throughput RNA Genetic Engineering

Stimmen zu »Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology«

Details

ISBN: 9781071626160
Verlag: Springer US
Erscheinung: 14.10.2022

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