Machine Learning and Big Data-enabled Biotechnology
portes grátis
Machine Learning and Big Data-enabled Biotechnology
Alper, Hal S.
Wiley-VCH Verlag GmbH
03/2026
432
Dura
Inglês
9783527354740
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
Preface
Chapter 1: From genome to actionable insights in biotechnology
James Morrissey, Benjamin Strain, Cleo Kontoravdi
Chapter 2: Automated approaches for the development of genome-scale metabolic network models
Emma M. Glass, Deborah A. Powers, Jason A. Papin
Chapter 3: Machine-guided approaches for synthetic biology part design
Marc Amil, Leandro N. Ventimiglia, Aleksej Zelezniak
Chapter 4: Machine Learning for Sequence-to-Function Approaches
Rana A. Barghout, Maxim Kirby, Austin Zheng, Lya Chinas, Marjan Mohammadi, Zhiqing Xu, Benjamin Sanchez-Lengeling, and Radhakrishnan Mahadevan
Chapter 5: Prediction of Enzyme Functions by Artificial Intelligence
Ha Rim Kim, Hongkeun Ji, Gi Bae Kim, and Sang Yup Lee
Chapter 6: Design of Biochemical Pathways via AI/ML enabled Retrobiosynthesis
Hongxiang Li, Xuan Liu, and Huimin Zhao
Chapter 7: Machine learning to accelerate the discovery of therapeutic peptides
Nicole Soto-Garcia, Mehdi D. Davari, and David Medina-Ortiz
Chapter 8: Machine Learning Approaches for HTP Microbial Identification/Culturing
Mohamed Mastouri, Yang Zhang
Chapter 9: Generative AI for Knowledge Mining of Synthetic Biology and Bioprocess Engineering Literature
Zhengyang Xiao, Yinjie J. Tang
Chapter 10: Metabolomics big data approaches
Kenya Tanaka, Christopher J. Vavricka, Tomohisa Hasunuma
Chapter 11: Strain engineering, flux design, and metabolic production using Big Data: Ongoing advances and opportunities
Rafael S. Costa and Rui Henriques
Chapter 12: Next-generation metabolic flux analysis using machine learning
Ahmed Almunaifi, Richard C. Law, Samantha O'Keeffe, Kartikeya Pande, Tongjun Xiang, Onyedika Ukwueze, Aranaa Odai-Okley, Pin-Kuang Lai, Junyoung O. Park
Chapter 13: Streamlining the Design-Build-Test-Learn Process in Automated Biofoundries
Enrico Orsi, Nicolas Gurdo, and Pablo I. Nikel
Chapter 14: Machine Learning-Enhanced Hybrid Modeling for Phenotype Prediction and Bioreactor Optimization
Oliver Pennington, Yirong Chen, Youping Xie, and Dongda Zhang
Chapter 1: From genome to actionable insights in biotechnology
James Morrissey, Benjamin Strain, Cleo Kontoravdi
Chapter 2: Automated approaches for the development of genome-scale metabolic network models
Emma M. Glass, Deborah A. Powers, Jason A. Papin
Chapter 3: Machine-guided approaches for synthetic biology part design
Marc Amil, Leandro N. Ventimiglia, Aleksej Zelezniak
Chapter 4: Machine Learning for Sequence-to-Function Approaches
Rana A. Barghout, Maxim Kirby, Austin Zheng, Lya Chinas, Marjan Mohammadi, Zhiqing Xu, Benjamin Sanchez-Lengeling, and Radhakrishnan Mahadevan
Chapter 5: Prediction of Enzyme Functions by Artificial Intelligence
Ha Rim Kim, Hongkeun Ji, Gi Bae Kim, and Sang Yup Lee
Chapter 6: Design of Biochemical Pathways via AI/ML enabled Retrobiosynthesis
Hongxiang Li, Xuan Liu, and Huimin Zhao
Chapter 7: Machine learning to accelerate the discovery of therapeutic peptides
Nicole Soto-Garcia, Mehdi D. Davari, and David Medina-Ortiz
Chapter 8: Machine Learning Approaches for HTP Microbial Identification/Culturing
Mohamed Mastouri, Yang Zhang
Chapter 9: Generative AI for Knowledge Mining of Synthetic Biology and Bioprocess Engineering Literature
Zhengyang Xiao, Yinjie J. Tang
Chapter 10: Metabolomics big data approaches
Kenya Tanaka, Christopher J. Vavricka, Tomohisa Hasunuma
Chapter 11: Strain engineering, flux design, and metabolic production using Big Data: Ongoing advances and opportunities
Rafael S. Costa and Rui Henriques
Chapter 12: Next-generation metabolic flux analysis using machine learning
Ahmed Almunaifi, Richard C. Law, Samantha O'Keeffe, Kartikeya Pande, Tongjun Xiang, Onyedika Ukwueze, Aranaa Odai-Okley, Pin-Kuang Lai, Junyoung O. Park
Chapter 13: Streamlining the Design-Build-Test-Learn Process in Automated Biofoundries
Enrico Orsi, Nicolas Gurdo, and Pablo I. Nikel
Chapter 14: Machine Learning-Enhanced Hybrid Modeling for Phenotype Prediction and Bioreactor Optimization
Oliver Pennington, Yirong Chen, Youping Xie, and Dongda Zhang
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synthetic biology; GSM development; De novo protein structure; pathway discovery; retrobiosynthesis; enzyme functional classifications; proteomics; Metabolomics; strain engineering; flux design; cell models; biofoundries; bioreactor
Preface
Chapter 1: From genome to actionable insights in biotechnology
James Morrissey, Benjamin Strain, Cleo Kontoravdi
Chapter 2: Automated approaches for the development of genome-scale metabolic network models
Emma M. Glass, Deborah A. Powers, Jason A. Papin
Chapter 3: Machine-guided approaches for synthetic biology part design
Marc Amil, Leandro N. Ventimiglia, Aleksej Zelezniak
Chapter 4: Machine Learning for Sequence-to-Function Approaches
Rana A. Barghout, Maxim Kirby, Austin Zheng, Lya Chinas, Marjan Mohammadi, Zhiqing Xu, Benjamin Sanchez-Lengeling, and Radhakrishnan Mahadevan
Chapter 5: Prediction of Enzyme Functions by Artificial Intelligence
Ha Rim Kim, Hongkeun Ji, Gi Bae Kim, and Sang Yup Lee
Chapter 6: Design of Biochemical Pathways via AI/ML enabled Retrobiosynthesis
Hongxiang Li, Xuan Liu, and Huimin Zhao
Chapter 7: Machine learning to accelerate the discovery of therapeutic peptides
Nicole Soto-Garcia, Mehdi D. Davari, and David Medina-Ortiz
Chapter 8: Machine Learning Approaches for HTP Microbial Identification/Culturing
Mohamed Mastouri, Yang Zhang
Chapter 9: Generative AI for Knowledge Mining of Synthetic Biology and Bioprocess Engineering Literature
Zhengyang Xiao, Yinjie J. Tang
Chapter 10: Metabolomics big data approaches
Kenya Tanaka, Christopher J. Vavricka, Tomohisa Hasunuma
Chapter 11: Strain engineering, flux design, and metabolic production using Big Data: Ongoing advances and opportunities
Rafael S. Costa and Rui Henriques
Chapter 12: Next-generation metabolic flux analysis using machine learning
Ahmed Almunaifi, Richard C. Law, Samantha O'Keeffe, Kartikeya Pande, Tongjun Xiang, Onyedika Ukwueze, Aranaa Odai-Okley, Pin-Kuang Lai, Junyoung O. Park
Chapter 13: Streamlining the Design-Build-Test-Learn Process in Automated Biofoundries
Enrico Orsi, Nicolas Gurdo, and Pablo I. Nikel
Chapter 14: Machine Learning-Enhanced Hybrid Modeling for Phenotype Prediction and Bioreactor Optimization
Oliver Pennington, Yirong Chen, Youping Xie, and Dongda Zhang
Chapter 1: From genome to actionable insights in biotechnology
James Morrissey, Benjamin Strain, Cleo Kontoravdi
Chapter 2: Automated approaches for the development of genome-scale metabolic network models
Emma M. Glass, Deborah A. Powers, Jason A. Papin
Chapter 3: Machine-guided approaches for synthetic biology part design
Marc Amil, Leandro N. Ventimiglia, Aleksej Zelezniak
Chapter 4: Machine Learning for Sequence-to-Function Approaches
Rana A. Barghout, Maxim Kirby, Austin Zheng, Lya Chinas, Marjan Mohammadi, Zhiqing Xu, Benjamin Sanchez-Lengeling, and Radhakrishnan Mahadevan
Chapter 5: Prediction of Enzyme Functions by Artificial Intelligence
Ha Rim Kim, Hongkeun Ji, Gi Bae Kim, and Sang Yup Lee
Chapter 6: Design of Biochemical Pathways via AI/ML enabled Retrobiosynthesis
Hongxiang Li, Xuan Liu, and Huimin Zhao
Chapter 7: Machine learning to accelerate the discovery of therapeutic peptides
Nicole Soto-Garcia, Mehdi D. Davari, and David Medina-Ortiz
Chapter 8: Machine Learning Approaches for HTP Microbial Identification/Culturing
Mohamed Mastouri, Yang Zhang
Chapter 9: Generative AI for Knowledge Mining of Synthetic Biology and Bioprocess Engineering Literature
Zhengyang Xiao, Yinjie J. Tang
Chapter 10: Metabolomics big data approaches
Kenya Tanaka, Christopher J. Vavricka, Tomohisa Hasunuma
Chapter 11: Strain engineering, flux design, and metabolic production using Big Data: Ongoing advances and opportunities
Rafael S. Costa and Rui Henriques
Chapter 12: Next-generation metabolic flux analysis using machine learning
Ahmed Almunaifi, Richard C. Law, Samantha O'Keeffe, Kartikeya Pande, Tongjun Xiang, Onyedika Ukwueze, Aranaa Odai-Okley, Pin-Kuang Lai, Junyoung O. Park
Chapter 13: Streamlining the Design-Build-Test-Learn Process in Automated Biofoundries
Enrico Orsi, Nicolas Gurdo, and Pablo I. Nikel
Chapter 14: Machine Learning-Enhanced Hybrid Modeling for Phenotype Prediction and Bioreactor Optimization
Oliver Pennington, Yirong Chen, Youping Xie, and Dongda Zhang
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
