Artificial Intelligence in Drug Design [E-Book] / edited by Alexander Heifetz.
This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand...
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Full text |
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Personal Name(s): | Heifetz, Alexander, editor |
Edition: |
1st edition 2022. |
Imprint: |
New York, NY :
Humana Press,
2022
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Physical Description: |
XI, 529 pages 103 illustrations, 89 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9781071617878 |
DOI: |
10.1007/978-1-0716-1787-8 |
Series Title: |
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Methods in Molecular Biology ;
2390 |
Subject (LOC): |
- Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
- Machine Learning Applied to the Modeling of Pharmacological and ADMET Endpoints
- Fighting COVID-19 with Artificial Intelligence
- Application of Artificial Intelligence and Machine Learning in Drug Discovery
- Deep Learning and Computational Chemistry
- Has Drug Design Augmented by Artificial Intelligence Become a Reality?
- Network Driven Drug Discovery
- Predicting Residence Time of GPCR Ligands with Machine Learning
- De Novo Molecular Design with Chemical Language Models
- Deep Neural Networks for QSAR
- Deep Learning in Structure-Based Drug Design
- Deep Learning Applied to Ligand-Based De Novo Drug Design
- Ultra-High Throughput Protein-Ligand Docking with Deep Learning
- Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors
- Artificial Intelligence in Compound Design
- Artificial Intelligence, Machine Learning, and Deep Learning in Real Life Drug Design Cases
- Artificial Intelligence-Enabled De Novo Design of Novel Compounds that are Synthesizable
- Machine Learning from Omics Data
- Deep Learning in Therapeutic Antibody Development
- Machine Learning for In Silico ADMET Prediction
- Opportunities and Considerations in the Application of Artificial Intelligence to Pharmacokinetic Prediction
- Artificial Intelligence in Drug Safety and Metabolism
- Molecule Ideation Using Matched Molecular Pairs.