Revolutionizing Drug Development by Chen, Jen-Tsung;

Harnessing AI and Computational Biology

20% KEDVEZMÉNY?
A kedvezmény csak az 'Értesítés a kedvenc témákról' hírlevelünk címzettjeinek rendeléseire érvényes.

Kiadói listaár EUR 162.99
Az ár azért becsült, mert a rendelés pillanatában nem lehet pontosan tudni, hogy a beérkezéskor milyen lesz a forint árfolyama az adott termék eredeti devizájához képest. Ha a forint romlana, kissé többet, ha javulna, kissé kevesebbet kell majd fizetnie.

67 600 Ft (64 381 Ft + 5% áfa)
Kedvezmény(ek) 20% (cc. 13 520 Ft off)
Kedvezményes ár 54 080 Ft (51 505 Ft + 5% áfa)

67 600 Ft

Beszerezhetőség

Még nem jelent meg, de rendelhető. A megjelenéstől számított néhány héten belül megérkezik.

A termék adatai:

Kiadó Elsevier Science
Megjelenés dátuma 2026. január 1.

ISBN 9780443340598
Kötéstípus Puhakötés
Terjedelem230 oldal
Méret 276x216 mm
Nyelv angol

Kategóriák

A biológia általános kérdései A biológia általános kérdései (karitatív célú kampány)

Hosszú leírás:

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.

Több

Tartalomjegyzék:

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