Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied
as an evaluative approach, ie, with the focus on developing retrospective and explanatory …

Quantitative structure-activity relationship (QSAR) modeling is themajor cheminformatics
approach to exploring and exploiting the dependency of chemical, biological, toxicological …

This perspective concerns the methods employed within the current drug discovery
community to develop predictive quantitative structure–activity relationships (QSAR) …

Quantitative structure–activity relationship modeling is one of the major computational tools
employed in medicinal chemistry. However, throughout its entire history it has drawn both …

Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …

Introduction: Quantitative structure-activity/property relationships (QSAR/QSPR) are
statistical models which quantitatively correlate quantitative chemical structure information …

Quantitative structure-activity relationship (QSAR) modeling pertains to the construction of
predictive models of biological activities as a function of structural and molecular information …

Deriving quantitative structure− activity relationship (QSAR) models that are accurate,
reliable, and easily interpretable is a difficult task. In this study, two new methods have been …

Quantitative structure‐activity/property/toxicity relationship (QSAR/QSPR/QSTR) models are
effectively employed to fill data gaps by predicting a given response from known structural …

Quantitative structure-activity relationships (QSARs) have important applications in drug
discovery research, environmental fate modeling, property prediction, etc. Validation has …