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| Language | English |
| Format | PDF (Premium Digital) |
| Ownership | Permanent download — yours forever |
Artificial Intelligence in Drug Design 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-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls.| SKU | NLS9781071617892 |
|---|---|
| ISBN 13 | 9781071617892 |
| ISBN 10 | 1071617893 |
| Author | Alexander Heifetz |
| Series | Methods In Molecular Biology |
| Condition | New |
| Binding Type | Paperback |
| Publisher | Springer-Verlag New York Inc. |
| Year published | 2022-11-05 |
| Number of pages | 529 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
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