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

Quantitative Structure–Activity Relationship (QSAR) is a popular approach developed to
correlate chemical molecules with their biological activities based on their chemical …

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

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

Abstract Quantitative Structure–Activity Relationship (QSAR) models are used increasingly
to screen chemical databases and/or virtual chemical libraries for potentially bioactive …

After nearly five decades “in the making”, QSAR modeling has established itself as one of
the major computational molecular modeling methodologies. As any mature research …

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

Background In-silico quantitative structure–activity relationship (QSAR) models based tools
are widely used to screen huge databases of compounds in order to determine the …

Quantitative structure—activity relationships (QSARs) attempt to correlate chemical structure
with activity using statistical approaches. The QSAR models are useful for various purposes …