In QSAR, a statistical model is generated from a training set of molecules (represented by
chemical descriptors) and their biological activities (an “activity model”). The aim of the field …

In QSAR, a statistical model is generated from a training set of molecules (represented by
chemical descriptors) and their biological activities. We will call this traditional type of QSAR …

One popular metric for estimating the accuracy of prospective quantitative structure–activity
relationship (QSAR) predictions is based on the similarity of the compound being predicted …

How well can a QSAR model predict the activity of a molecule not in the training set used to
create the model? A set of retrospective cross-validation experiments using 20 diverse in …

When QSAR models are fitted, it is important to validate any fitted model to check that it is
plausible that its predictions will carry over to fresh data not used in the model fitting …

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

The vastness of chemical space and the relatively small coverage by experimental data
recording molecular properties require us to identify subspaces, or domains, for which we …

Background With the growing popularity of using QSAR predictions towards regulatory
purposes, such predictive models are now required to be strictly validated, an essential …

Predictability and prediction reliability are of utmost important to characterize a good
Quantitative structure–activity relationships (QSAR) model. However, validation methods are …

We introduce a simple MODelability Index (MODI) that estimates the feasibility of obtaining
predictive QSAR models (correct classification rate above 0.7) for a binary data set of …