q-RASAR

A Path to Predictive Cheminformatics

von Kunal Roy, Arkaprava Banerjee

91 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

• Reihe: SpringerBriefs in Molecular Science
• Themen: Mathematik und Naturwissenschaften Chemie Physikalische Chemie Chemoinformatik
• ISBN: 9783031520563
• Sprache: Englisch
• Erscheinungsdatum: 26.01.2024
• Größe: 23.5 x 15.5 cm
• Verlag: Springer International Publishing