Cantitate/Preț
Produs

Computational Approaches in Drug Discovery, Development and Systems Pharmacology

Editat de Rupesh Kumar Gautam, Mohammad Amjad Kamal, Pooja Mittal
en Limba Engleză Paperback – 25 ian 2023
Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics.

  • Explains computer use in pharmacology using real-life case studies
  • Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research
  • Describes the role of AI in pharmacology and applications of CADD in various diseases
Citește tot Restrânge

Preț: 97833 lei

Preț vechi: 102982 lei
-5% Nou

Puncte Express: 1467

Preț estimativ în valută:
18724 19753$ 15604£

Carte disponibilă

Livrare economică 13-27 decembrie
Livrare express 28 noiembrie-04 decembrie pentru 3993 lei

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9780323991377
ISBN-10: 0323991378
Pagini: 362
Dimensiuni: 152 x 229 x 23 mm
Greutate: 0.6 kg
Editura: ELSEVIER SCIENCE

Public țintă

Researchers and academics working in the area of CADD, pharmacology and Bioinformatics

Cuprins

1. In sillico pharmacology
2. Computer aided drug design and drug discovery
3. Alternative biological screening methods
4. AI and deep machine learning in pharmacology
5. Pharmacophore modelling
6. Target identification and validation
7. New drug discovery pipeline
8. Virtual screening