Q-Rasar: A Path to Predictive Cheminformatics

By Kunal Roy and Arkaprava Banerjee

This brief offers an introduction to the fascinating new field of quantitative read-across structure-activity relationships (q-RASAR) as a cheminformatics modeling approach in the background of quantitative structure-activity relationships (QSAR) and read-across (RA) as data gap-filling methods. It discusses the genesis and model development of q-RASAR models demonstrating practical examples. It also showcases successful case studies on the application of q-RASAR modeling in medicinal chemistry, predictive toxicology, and materials sciences. The book also includes the tools used for q-RASAR model development for new users. It is a valuable resource for researchers and students interested in grasping the development algorithm of q-RASAR models and their application within specific research domains.

• Format: Paperback
• Language: English
• ISBN: 3031520564
• ISBN13: 9783031520563
• Release Date: January 2024
• Publisher: Springer
• Length: 91 Pages
• Weight: 0.35 lbs.
• Dimensions: 0.2" x 6.1" x 9.2"