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  • Revolutionizing Drug Development: Harnessing AI and Computational Biology

    Revolutionizing Drug Development by Chen, Jen-Tsung;

    Harnessing AI and Computational Biology

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 162.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        67 600 Ft (64 381 Ft + 5% VAT)
      • Discount 20% (cc. 13 520 Ft off)
      • Discounted price 54 080 Ft (51 505 Ft + 5% VAT)

    67 600 Ft

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    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Elsevier Science
    • Date of Publication 1 January 2026

    • ISBN 9780443340598
    • Binding Paperback
    • No. of pages230 pages
    • Size 276x216 mm
    • Language English
    • 700

    Categories

    Long description:

    Revolutionizing Drug Development: Harnessing AI and Computational Biology presents cutting-edge artificial intelligence (AI) tools, such as machine- and deep-learning models and generative AI, to assist structure-based drug design and clinical trial design and integrate with drug development programs. This book summarizes technical advancements of AI-based technologies and computational biology approaches, highlighting their applications in developing new drugs through discovery, repurposing, and designing, for advancing R&D in the pharmaceutical industry and benefiting precision medicine. This book serves as an ideal reference for students, teachers, professors, and researchers in biological and biomedical sciences, particularly the topics related to bioinformatics, systems biology, pharmacology, and drug development. The readers can efficiently and precisely overview this burning field, which might inspire their future directions of research in drug development and AI-based digital biology.

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    Table of Contents:

    Artificial intelligence and accelerated computing in drug discovery: An updated overview
    2. AI strategies for drug discovery and bioactivity prediction: Opportunities and challenges
    3. AI technologies for drug repurposing: Methods and applications
    4. Data science and databases in drug discovery: Technical development and applications
    5. Graph neural networks for drug discovery: Protocols and applications
    6. Deep learning and generative models for drug discovery: Techniques and current achievements
    7. AI-enabled personalized medicine: Strategies and challenges
    8. AI technologies for advancing R&D in the pharmaceutical industry: Current development and challenges
    10. AI-powered drug development for treating neurological disorders
    11. AI applications in drug discovery for promoting longevity
    12. Transforming Drug Development with AI-driven Models
    13. AI technologies for precision and personalized medicine
    14. AI technologies for smart pharmacology
    15. AI-powered Immunopharmacological strategies to combat inflammatory diseases
    16. AI and nanotechnology for advancing drug development
    17. Drug repositioning using tensor decomposition
    18. Integrating Artificial Intelligence and machine learning technologies in antiviral drug discovery: Strategies and challenges
    19. Artificial intelligence in the discovery of new antibiotics
    20. AI-designed drugs: Clinical development and future directions

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