Science, Nature & Maths      Biological Sciences

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

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Book Details
Language
English
Publishers
Springer; 1st ed. 2024 edition (26 Jan. 2024)
Weight
0.16 KG
Publication Date
01/03/2024
ISBN-10
3031520564
Pages
101 pages
ISBN-13
9783031520563
Dimensions
15.5 x 0.61 x 23.5 cm
SKU
9783031520563
Author Name
Kunal Roy (Author)
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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. .

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