This volume explores the application of high-performance computing
(HPC) technologies to computational drug discovery (CDD) and
biomedicine. The first section collects CDD approaches that,
together with HPC, can revolutionize and automate drug discovery
process, such as knowledge graphs, natural language processing
(NLP), Bayesian optimization, automated virtual screening
platforms, alchemical free energy workflows, fragment-molecular
orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC),
and the potential of cloud computing for drug discovery. The second
section delves into computational algorithms and workflows for
biomedicine, featuring an HPC framework to assess drug-induced
arrhythmic risk, digital patient applications relevant to the
clinic, virtual human simulations, cellular and whole-body blood
flow modeling for stroke treatments, prediction of the femoral bone
strength from CT data, and many more subjects. Written for
the highly successful Methods in Molecular
Biology series, chapters include introductions to their
respective topics, lists of the necessary software and tools,
step-by-step and readily reproducible modeling protocols, and tips
on troubleshooting and avoiding known pitfalls.Â
Authoritative and practical, High Performance Computing for Drug
Discovery and Biomedicine allows a diverse audience, including
computer scientists, computational and medicinal chemists,
biologists, clinicians, pharmacologists and drug designers, to
navigate the complex landscape of what is currently possible and to
understand the challenges and future directions of HPC-based
technologies.
General
Imprint: |
Springer-Verlag New York
|
Country of origin: |
United States |
Series: |
Methods in Molecular Biology, 2716 |
Release date: |
September 2023 |
First published: |
2023 |
Editors: |
Alexander Heifetz
|
Dimensions: |
254 x 178mm (L x W) |
Pages: |
436 |
Edition: |
1st ed. 2023 |
ISBN-13: |
978-1-07-163448-6 |
Categories: |
Books
Promotions
|
LSN: |
1-07-163448-8 |
Barcode: |
9781071634486 |
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