Artificial intelligence cell genetic (22 résultats)

Taschenbuch. Etat : Neu. Artificial Intelligence (AI) in Cell and Genetic Engineering | Sudip Mandal | Taschenbuch | Methods in Molecular Biology | xii | Englisch | 2026 | Springer | EAN 9781071646922 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. 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.Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering.…

Etat : New.

Hardcover. Etat : new. Hardcover. This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. 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.Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New. 2025. hardcover. . . . . .

Etat : New.

Hardcover. Etat : Brand New. 516 pages. 10.00x7.00x10.00 inches. In Stock.

Etat : New. 2025. hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Etat : new. Hardcover. This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. 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.Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Etat : new. Questo è un articolo print on demand.

Hardcover. Etat : Brand New. 516 pages. 10.00x7.00x10.00 inches. In Stock. This item is printed on demand.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. 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.Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 508 pp. Englisch.…

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. 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.Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering. 508 pp. Englisch.…

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. 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.Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 508 pp. Englisch.…

Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. 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.Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering.…

Etat : New. Print on Demand.

Etat : New. PRINT ON DEMAND.