q-RASAR : A Path to Predictive Cheminformatics (Springerbriefs in Molecular Science)

Roy, Kunal/ Banerjee, Arkaprava

Springer International Publishing AG（2024/01発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 91 p.
• 言語 ENG
• 商品コード 9783031520563

Full Description

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.

Contents

Chemical Information and Molecular Similarity.- Read-across and Quantitative Structure-activity Relationships (QSAR) for Making Predictions and Data Gap-Filling.- Quantitative Read-Across (q-RA) and Quantitative Read-Across Structure-Activity Relationships (q-RASAR) - Genesis and Model Development.- Tools, Applications, and Case Studies (q-RA and q-RASAR).- Future Prospects.