This volume describes the latest developments in using Artificial Intelligence (AI) and machine learning in the field of genomics. The chapters in this book cover a variety of topics such as ways to derive the biomarker and measure biological and pathological processes from transcriptomic data sets; techniques to infer the function of epigenetics using network-based methodology; a look at how CellOracle can figure out which gene-gene interaction is important; how to find a machine learning approach to figure out how microRNA affects the cardiovascular events; protocols on ways to find how AI/ML approaches can attack somatic variant detection in normal human tissue; and a description on how gene embeddings are powerful tools for predicting unknown functions of genes and drugs. 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.
Thorough and comprehensive, AI/ML-Driven Gene Analysis: Methods and Protocols is a valuable tool for researchers interested in learning more about how cutting-edge methodology for AI/ML is applied to genomics.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. This volume describes the latest developments in using Artificial Intelligence (AI) and machine learning in the field of genomics. The chapters in this book cover a variety of topics such as ways to derive the biomarker and measure biological and pathological processes from transcriptomic data sets; techniques to infer the function of epigenetics using network-based methodology; a look at how CellOracle can figure out which gene-gene interaction is important; how to find a machine learning approach to figure out how microRNA affects the cardiovascular events; protocols on ways to find how AI/ML approaches can attack somatic variant detection in normal human tissue; and a description on how gene embeddings are powerful tools for predicting unknown functions of genes and drugs. 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.Thorough and comprehensive, AI/ML-Driven Gene Analysis: Methods and Protocols is a valuable tool for researchers interested in learning more about how cutting-edge methodology for AI/ML is applied to genomics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781071652831
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. N° de réf. du vendeur 2901136401
Quantité disponible : Plus de 20 disponibles
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume describes the latest developments in using Artificial Intelligence (AI) and machine learning in the field of genomics. The chapters in this book cover a variety of topics such as ways toderive the biomarker and measure biological and pathological processes from transcriptomic data sets; techniques to infer the function of epigenetics using network-based methodology; a look at how CellOracle can figure out which gene-gene interaction is important; how to find a machine learning approach to figure out how microRNA affects the cardiovascular events; protocols on ways to find how AI/ML approaches can attack somatic variant detection in normal human tissue; and a description on how gene embeddings are powerful tools for predicting unknown functions of genes and drugs. Written in the highly successfulMethods in Molecular Biologyseries 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.Thorough and comprehensive,AI/ML-Driven Gene Analysis: Methods and Protocolsis a valuable tool for researchers interested in learning more about how cutting-edge methodology for AI/ML is applied to genomics. 268 pp. Englisch. N° de réf. du vendeur 9781071652831
Quantité disponible : 2 disponible(s)
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. This volume describes the latest developments in using Artificial Intelligence (AI) and machine learning in the field of genomics. The chapters in this book cover a variety of topics such as ways to derive the biomarker and measure biological and pathological processes from transcriptomic data sets; techniques to infer the function of epigenetics using network-based methodology; a look at how CellOracle can figure out which gene-gene interaction is important; how to find a machine learning approach to figure out how microRNA affects the cardiovascular events; protocols on ways to find how AI/ML approaches can attack somatic variant detection in normal human tissue; and a description on how gene embeddings are powerful tools for predicting unknown functions of genes and drugs. 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.Thorough and comprehensive, AI/ML-Driven Gene Analysis: Methods and Protocols is a valuable tool for researchers interested in learning more about how cutting-edge methodology for AI/ML is applied to genomics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781071652831
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume describes the latest developments in using Artificial Intelligence (AI) and machine learning in the field of genomics. The chapters in this book cover a variety of topics such as ways toderive the biomarker and measure biological and pathological processes from transcriptomic data sets; techniques to infer the function of epigenetics using network-based methodology; a look at how CellOracle can figure out which gene-gene interaction is important; how to find a machine learning approach to figure out how microRNA affects the cardiovascular events; protocols on ways to find how AI/ML approaches can attack somatic variant detection in normal human tissue; and a description on how gene embeddings are powerful tools for predicting unknown functions of genes and drugs. Written in the highly successfulMethods in Molecular Biologyseries 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.Thorough and comprehensive,AI/ML-Driven Gene Analysis: Methods and Protocolsis a valuable tool for researchers interested in learning more about how cutting-edge methodology for AI/ML is applied to genomics. N° de réf. du vendeur 9781071652831
Quantité disponible : 1 disponible(s)
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This volume describes the latest developments in using Artificial Intelligence (AI) and machine learning in the field of genomics. The chapters in this book cover a variety of topics such as ways to derive the biomarker and measure biological and pathological processes from transcriptomic data sets; techniques to infer the function of epigenetics using network-based methodology; a look at how CellOracle can figure out which gene-gene interaction is important; how to find a machine learning approach to figure out how microRNA affects the cardiovascular events; protocols on ways to find how AI/ML approaches can attack somatic variant detection in normal human tissue; and a description on how gene embeddings are powerful tools for predicting unknown functions of genes and drugs. 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.Thorough and comprehensive, AI/ML-Driven Gene Analysis: Methods and Protocols is a valuable tool for researchers interested in learning more about how cutting-edge methodology for AI/ML is applied to genomics.Springer Nature Customer Service Center GmbH, Europaplatz 3,69115 Heidelberg, Germany, 69115 Heidelberg 280 pp. Englisch. N° de réf. du vendeur 9781071652831
Quantité disponible : 1 disponible(s)
Vendeur : Books Puddle, Woodside, NY, Etats-Unis
Etat : New. N° de réf. du vendeur 26405608948
Quantité disponible : 4 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand. N° de réf. du vendeur 408593963
Quantité disponible : 4 disponible(s)
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND. N° de réf. du vendeur 18405608958
Quantité disponible : 4 disponible(s)
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Hardcover. Etat : new. Hardcover. This volume describes the latest developments in using Artificial Intelligence (AI) and machine learning in the field of genomics. The chapters in this book cover a variety of topics such as ways to derive the biomarker and measure biological and pathological processes from transcriptomic data sets; techniques to infer the function of epigenetics using network-based methodology; a look at how CellOracle can figure out which gene-gene interaction is important; how to find a machine learning approach to figure out how microRNA affects the cardiovascular events; protocols on ways to find how AI/ML approaches can attack somatic variant detection in normal human tissue; and a description on how gene embeddings are powerful tools for predicting unknown functions of genes and drugs. 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.Thorough and comprehensive, AI/ML-Driven Gene Analysis: Methods and Protocols is a valuable tool for researchers interested in learning more about how cutting-edge methodology for AI/ML is applied to genomics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781071652831
Quantité disponible : 1 disponible(s)