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Artificial Intelligence in Drug Design

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Cover of 'Artificial Intelligence in Drug Design'

Table of Contents

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    Book Overview
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    Chapter 1 Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
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    Chapter 2 Machine Learning Applied to the Modeling of Pharmacological and ADMET Endpoints
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    Chapter 3 Fighting COVID-19 with Artificial Intelligence
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    Chapter 4 Application of Artificial Intelligence and Machine Learning in Drug Discovery
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    Chapter 5 Deep Learning and Computational Chemistry
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    Chapter 6 Has Artificial Intelligence Impacted Drug Discovery?
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    Chapter 7 Network-Driven Drug Discovery
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    Chapter 8 Predicting Residence Time of GPCR Ligands with Machine Learning.
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    Chapter 9 De Novo Molecular Design with
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    Chapter 10 Deep Neural for QSAR
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    Chapter 11 Deep Learning in
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    Chapter 12 Deep Learning Applied to Ligand-Based
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    Chapter 13 Ultrahigh Throughput Protein–Ligand with Deep Learning
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    Chapter 14 Artificial Intelligence and Quantum as the Next Pharma Disruptors
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    Chapter 15 Artificial Intelligence in Compound Design
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    Chapter 16 Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases
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    Chapter 17 Artificial Intelligence–Enabled of Novel Compounds that Are Synthesizable
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    Chapter 18 Machine Learning from Omics Data.
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    Chapter 19 Deep Learning in Therapeutic
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    Chapter 20 Machine Learning for Prediction
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    Chapter 21 Opportunities and Considerations in the Application of Artificial Intelligence to Pharmacokinetic Prediction
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    Chapter 22 Artificial Intelligence in Drug Safety and Metabolism
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    Chapter 23 Molecule Ideation Using Matched Molecular
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

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