q-RASAR q-RASAR
SpringerBriefs in Molecular Science

q-RASAR

A Path to Predictive Cheminformatics

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Beschreibung 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.

GENRE
Wissenschaft und Natur
ERSCHIENEN
2024
25. Januar
SPRACHE
EN
Englisch
UMFANG
101
Seiten
VERLAG
Springer Nature Switzerland
GRÖSSE
7.4
 MB
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