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Computational Modeling of Drugs Against Alzheimers Disease Second Edition 2023 [Hardback]

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  • Formāts: Hardback, 493 pages, height x width: 254x178 mm, weight: 1150 g, 122 Illustrations, color; 54 Illustrations, black and white; XVII, 493 p. 176 illus., 122 illus. in color. With online files/update., 1 Hardback
  • Sērija : Neuromethods 203
  • Izdošanas datums: 01-Jul-2023
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1071633104
  • ISBN-13: 9781071633106
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  • Formāts: Hardback, 493 pages, height x width: 254x178 mm, weight: 1150 g, 122 Illustrations, color; 54 Illustrations, black and white; XVII, 493 p. 176 illus., 122 illus. in color. With online files/update., 1 Hardback
  • Sērija : Neuromethods 203
  • Izdošanas datums: 01-Jul-2023
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1071633104
  • ISBN-13: 9781071633106
Citas grāmatas par šo tēmu:
This second edition volume expands on the previous edition with updated descriptions on different computational methods encompassing ligand-based, structure-based, and combined approaches with their recent applications in anti-Alzheimer drug design. Different background topics like recent advancements in research on the development of novel therapies and their implications in the treatment of Alzheimer’s Disease (AD) have also been covered for completeness. Special topics like basic information science methods for insight into neurodegenerative pathogenesis, drug repositioning and network pharmacology, and online tools to predict ADMET behavior with reference to anti-Alzheimer drug development have also been included. In the Neuromethods series style, chapter include the kind of detail and key advice from the specialists needed to get successful results in your laboratory.

Cutting-edge and thorough, Computational Modeling of Drugs Against Alzheimer’s Disease, Second Edition is a valuable resource for all researchers and scientists interested in learning more about this important and developing field.

Recent Progress in the Treatment Strategies of Alzheimers
Disease.- Understanding the Mechanisms of Amyloid Beta (A) Aggregation by
Computational Modeling.- Recent Advances in Computational Modeling of BACE1
Inhibitors as Anti-Alzheimer Agents.- Modeling of BACE-1 Inhibitors as
Anti-Alzheimers Agents.- Computational Modeling of Kinase Inhibitors as
Anti-Alzheimer Agents.- Computer-Assisted Drug Design: A Toolbox for Novel
Tau Kinase Inhibitors and Its Implications in Alzheimers
Disease.- Computational Modeling Approaches in Search of Anti-Alzheimer
Agents: Case Studies of Phosphodiesterase Inhibitors.- Recent Advances in
Computational Modeling of Multi-Targeting Inhibitors as Anti-Alzheimer
Agents.- Computational Modeling of PET and SPECT Imaging Agents as
Diagnostics for Alzheimers Disease.- Computational Modeling of DYRK1A
Inhibitors as Potential Anti-Alzheimer Agents.- Computational Modeling of MAO
Inhibitors as Anti-Alzheimer Agents.- Computational Modeling of
Phosphodiesterase Inhibitors as Anti-Alzheimer Agents.- Computational Methods
for the Design and Development of Glutaminyl Cyclase Inhibitors in
Alzheimers Disease.- Basic Information Science Methods for Insight into
Neurodegenerative Pathogenesis.- Network Pharmacology for Drug Repositioning
in Anti-Alzheimer's Drug Development.- Web Services for the Prediction of
ADMET Parameters Relevant to the Design of Neuroprotective Drugs.