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Artificial Intelligence in Drug Design

Overview of attention for book
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
Attention for Chapter 15: Artificial Intelligence in Compound Design
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Chapter title
Artificial Intelligence in Compound Design
Chapter number 15
Book title
Artificial Intelligence in Drug Design
Published by
Humana, New York, NY, November 2021
DOI 10.1007/978-1-0716-1787-8_15
Pubmed ID
Book ISBNs
978-1-07-161786-1, 978-1-07-161787-8
Authors

Grebner, Christoph, Matter, Hans, Hessler, Gerhard

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 21%
Unspecified 2 14%
Researcher 1 7%
Student > Doctoral Student 1 7%
Lecturer 1 7%
Other 0 0%
Unknown 6 43%
Readers by discipline Count As %
Unspecified 2 14%
Chemistry 2 14%
Business, Management and Accounting 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Computer Science 1 7%
Other 1 7%
Unknown 6 43%