Artificial Intelligence in Drug Design (Hardcover, 1st ed. 2022)

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. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Methods in Molecular Biology, 2390
Release date:	November 2021
Editors:	Alexander Heifetz
Dimensions:	254 x 178mm (L x W)
Format:	Hardcover
Pages:	529
Edition:	1st ed. 2022
ISBN-13:	978-1-07-161786-1
Categories:	Books > Medicine > Other branches of medicine > Pharmacology > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	1-07-161786-9
Barcode:	9781071617861

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