ML for Target Identification & Validation in Drug Discovery: Optimizing Drug Targeting - ML Techniques - Softcover
Synopsis
Machine Learning Approaches for Target Identification and Validation in Drug Discovery examines the transformative role of machine learning (ML) in enhancing the drug discovery process. The introduction highlights the importance of accurate target identification and validation, while subsequent sections delve into various ML algorithms for predicting potential drug targets based on biological data. Gene prioritization methods are discussed, showcasing how ML can effectively rank disease-associated genes. Additionally, the integration of ML with knowledge graphs is explored, illustrating how these tools enhance data connectivity and decision-making. Finally, the importance of information extraction through data mining and natural language processing is addressed, illustrating how these approaches help researchers extract valuable insights from large datasets, thereby advancing the field of drug discovery.
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ML for Target Identification & Validation in Drug Discovery (Paperback)
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LAP Lambert Academic Publishing, 2024
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ISBN 13: 9783659469923
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Paperback. Condition: new. Paperback. Machine Learning Approaches for Target Identification and Validation in Drug Discovery examines the transformative role of machine learning (ML) in enhancing the drug discovery process. The introduction highlights the importance of accurate target identification and validation, while subsequent sections delve into various ML algorithms for predicting potential drug targets based on biological data. Gene prioritization methods are discussed, showcasing how ML can effectively rank disease-associated genes. Additionally, the integration of ML with knowledge graphs is explored, illustrating how these tools enhance data connectivity and decision-making. Finally, the importance of information extraction through data mining and natural language processing is addressed, illustrating how these approaches help researchers extract valuable insights from large datasets, thereby advancing the field of drug discovery. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783659469923
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ML for Target Identification and Validation in Drug Discovery
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ML for Target Identification & Validation in Drug Discovery
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ML for Target Identification and Validation in Drug Discovery
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ML for Target Identification & Validation in Drug Discovery
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ML for Target Identification & Validation in Drug Discovery
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ML for Target Identification & Validation in Drug Discovery
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Machine Learning Approaches for Target Identification and Validation in Drug Discovery examines the transformative role of machine learning (ML) in enhancing the drug discovery process. The introduction highlights the importance of accurate target identification and validation, while subsequent sections delve into various ML algorithms for predicting potential drug targets based on biological data. Gene prioritization methods are discussed, showcasing how ML can effectively rank disease-associated genes. Additionally, the integration of ML with knowledge graphs is explored, illustrating how these tools enhance data connectivity and decision-making. Finally, the importance of information extraction through data mining and natural language processing is addressed, illustrating how these approaches help researchers extract valuable insights from large datasets, thereby advancing the field of drug discovery. 56 pp. Englisch. Seller Inventory # 9783659469923
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ML for Target Identification & Validation in Drug Discovery
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ML for Target Identification & Validation in Drug Discovery
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ML for Target Identification & Validation in Drug Discovery (Paperback)
Published by
LAP Lambert Academic Publishing, 2024
ISBN 10: 3659469920
ISBN 13: 9783659469923
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Paperback. Condition: new. Paperback. Machine Learning Approaches for Target Identification and Validation in Drug Discovery examines the transformative role of machine learning (ML) in enhancing the drug discovery process. The introduction highlights the importance of accurate target identification and validation, while subsequent sections delve into various ML algorithms for predicting potential drug targets based on biological data. Gene prioritization methods are discussed, showcasing how ML can effectively rank disease-associated genes. Additionally, the integration of ML with knowledge graphs is explored, illustrating how these tools enhance data connectivity and decision-making. Finally, the importance of information extraction through data mining and natural language processing is addressed, illustrating how these approaches help researchers extract valuable insights from large datasets, thereby advancing the field of drug discovery. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9783659469923