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

COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought the
most severe disruptions to societies and economies since the Great Depression. Massive …

As defined by the European Commission, a nanomaterial is a natural, an incidental, or a
manufactured material containing particles in an unbound state or as an aggregate or …

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 …

Molecular modelers and cheminformaticians typically analyze experimental data generated
by other scientists. Consequently, when it comes to data accuracy, cheminformaticians are …

Evaluation of biological effects, both desired and undesired, caused by manufactured
nanoparticles (MNPs) is of critical importance for nanotechnology. Experimental studies, …

The estimation of the accuracy of predictions is a critical problem in QSAR modeling. The “distance
to model” can be defined as a metric that defines the similarity between the training …

Despite the success of protein kinase inhibitors as approved therapeutics, drug discovery
has focused on a small subset of kinase targets. Here we provide a thorough characterization …

Selecting most rigorous quantitative structure−activity relationship (QSAR) approaches is of
great importance in the development of robust and predictive models of chemical toxicity. To …

Background: Humans are exposed to thousands of man-made chemicals in the environment.
Some chemicals mimic natural endocrine hormones and, thus, have the potential to be …