| Description |
1 online resource (x, 91 pages) : illustrations (some color) |
| Series |
SpringerBriefs in molecular science, 2191-5415 |
|
SpringerBriefs in molecular science, 2191-5415
|
| 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 |
| Summary |
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 |
| Bibliography |
Includes bibliographical references |
| Notes |
Online resource; title from PDF title page (SpringerLink, viewed January 31, 2024) |
| Subject |
Cheminformatics.
|
|
Computational chemistry.
|
|
QSAR (Biochemistry)
|
| Genre/Form |
Electronic books
|
| Form |
Electronic book
|
| Author |
Banerjee, Arkaprava, author
|
| ISBN |
9783031520570 |
|
3031520572 |
|
