Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment

Nonfiction, Health & Well Being, Medical, Medical Science, Pharmacology, Computers
Cover of the book Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment by Kunal Roy, Supratik Kar, Rudra Narayan Das, Elsevier Science
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Author: Kunal Roy, Supratik Kar, Rudra Narayan Das ISBN: 9780128016336
Publisher: Elsevier Science Publication: March 3, 2015
Imprint: Academic Press Language: English
Author: Kunal Roy, Supratik Kar, Rudra Narayan Das
ISBN: 9780128016336
Publisher: Elsevier Science
Publication: March 3, 2015
Imprint: Academic Press
Language: English

Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles.  This book includes clear, introductory coverage of the statistical methods applied in QSAR and new QSAR techniques, such as HQSAR and G-QSAR.  Containing real-world examples that illustrate important methodologies, this book identifies QSAR as a valuable tool for many different applications, including drug discovery, predictive toxicology and risk assessment.  Written in a straightforward and engaging manner, this is the ideal resource for all those looking for general and practical knowledge of QSAR methods.

  • Includes numerous practical examples related to QSAR methods and applications
  • Follows the Organization for Economic Co-operation and Development principles for QSAR model development
  • Discusses related techniques such as structure-based design and the combination of structure- and ligand-based design tools
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Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles.  This book includes clear, introductory coverage of the statistical methods applied in QSAR and new QSAR techniques, such as HQSAR and G-QSAR.  Containing real-world examples that illustrate important methodologies, this book identifies QSAR as a valuable tool for many different applications, including drug discovery, predictive toxicology and risk assessment.  Written in a straightforward and engaging manner, this is the ideal resource for all those looking for general and practical knowledge of QSAR methods.

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