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 ...
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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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Add this copy of Q-Rasar: a Path to Predictive Cheminformatics to cart. $20.00, Sold by Zubal Books rated 4.0 out of 5 stars, ships from Cleveland, OH, UNITED STATES, published 2024 by Springer.
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New. Print on demand Contains: Illustrations, black & white, Illustrations, color. SpringerBriefs in Molecular Science . X, 91 p. 20 illus., 17 illus. in color. Intended for professional and scholarly audience.
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New. Contains: Illustrations, black & white, Illustrations, color. SpringerBriefs in Molecular Science . X, 91 p. 20 illus., 17 illus. in color. Intended for professional and scholarly audience.