This paper is an overview of the most significant and impactful interpretation approaches of
quantitative structure–activity relationship (QSAR) models, their development, and …

The goal of a quantitative structure–activity relationship (QSAR) model is to encode the
relationship between molecular structure and biological activity or physical property. Based …

Quantitative structure− activity relationship (QSAR), an important area of drug design and
discovery, searches information relating chemical structure to biological and pharmaceutical …

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

Given a particular descriptor/method combination, some quantitative structure–activity
relationship (QSAR) datasets are very predictive by random-split cross-validation while …

The present work proposes a unified conceptual framework to describe and quantify the
important issue of the Applicability Domains (AD) of Quantitative Structure− Activity …

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

Quantitative structure-activity relationships (QSAR) have been around for many years and
have been employed in numerous fields from drug design to environmental toxicology …

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

Abstract Quantitative Structure-Activity Relationships are widely acknowledged predictive
methods employed, for years, in organic and medicinal chemistry. More recently, they have …