Computational Methods in Drug Discovery and Repurposing for Cancer Therapy
eBook - ePub

Computational Methods in Drug Discovery and Repurposing for Cancer Therapy

  1. 456 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Computational Methods in Drug Discovery and Repurposing for Cancer Therapy

About this book

Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research as well as computational approaches for drug discovery and repurposing for cancer therapy. The book also provides detailed descriptions about target molecules, pathways, and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, pancreatic, glioblastoma, endometrial, and retinoblastoma, among others. This book is a valuable resource for researchers, students, and members of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients. - Discusses in silico remodeling of effective phytochemical compounds for discovering improved anticancer agents for substantial/significant cancer therapy - Covers potential tools of bioinformatics that are applied toward discovering new targets by drug repurposing and strategies to cure different types of cancers - Demonstrates the significance of computational and artificial intelligence approaches in anticancer drug discovery - Explores how these various advances can be integrated into a precision and personalized medicine approach that can eventually enhance patient care

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Yes, you can access Computational Methods in Drug Discovery and Repurposing for Cancer Therapy by Ganji Purnachandra Nagaraju,Venkatesan Amouda,Ampasala Dinakara Rao in PDF and/or ePUB format, as well as other popular books in Business & Business Intelligence. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2023
Print ISBN
9780443152801
eBook ISBN
9780443152818
Topic
Business
Subtopic
Business Intelligence
Index
Business

Table of contents

  1. Cover
  2. Front Matter
  3. Table of Contents
  4. Copyright
  5. Dedication
  6. Contributors
  7. About the editors
  8. Preface
  9. List of Illustrations
  10. List of Tables
  11. Chapter 1 : Computational approaches for anticancer drug design
  12. Chapter 2 : Molecular modeling approach for cancer drug therapy
  13. Chapter 3 : Discovery of anticancer therapeutics: Computational chemistry and Artificial Intelligence-assisted approach
  14. Chapter 4 : Artificial intelligence in oncological therapies
  15. Chapter 5 : Approach of artificial intelligence in colorectal cancer and in precision medicine
  16. Chapter 6 : Artificial intelligence in breast cancer: An opportunity for early diagnosis
  17. Chapter 7 : Quantitative structure-activity relationship and its application to cancer therapy
  18. Chapter 8 : Structure-based virtual screening for the identification of novel Greatwall kinase inhibitors
  19. Chapter 9 : Strategies for drug repurposing
  20. Chapter 10 : Principles of computational drug designing and drug repurposing—An algorithmic approach
  21. Chapter 11 : Drug discovery and repositioning for glioblastoma multiforme and low-grade astrocytic tumors
  22. Chapter 12 : Repurposing of phytocompounds-derived novel bioactive compounds possessing promising anticancer and cancer therapeutic efficacy through molecular docking, MD simulation, and drug-likeness/ADMET studies
  23. Chapter 13 : Old drugs and new opportunities—Drug repurposing in colon cancer prevention
  24. Chapter 14 : Repurposing cardiac glycosides as the hallmark of immunogenic modulators in cancer therapy
  25. Chapter 15 : Systems biology tools for the identification of potential drug targets and biological markers effective for cancer therapeutics
  26. Chapter 16 : Role of human body fluid biomarkers in liver cancer: A systematic review
  27. Chapter 17 : Study on biomarkers in endometrial cancer using transcriptome data: A machine learning approach
  28. Chapter 18 : Drug targeting PIWI like protein-piRNA complex, a novel paradigm in the therapeutic framework of retinoblastoma
  29. Chapter 19 : Emerging role of biosimilars: Focus on Bevacizumab and hepatocellular carcinoma
  30. Chapter 20 : Integrated computational approaches to aid precision medicine for cancer therapy: Present scenario and future prospects
  31. Index
  32. A