Highlights•We review machine learning methods/tools relevant to ligand-based virtual
screening.•Machine learning methods classify compounds and predict new active …

Complex diseases (eg, Alzheimer's disease) or infectious diseases are usually caused by
complicated and varied factors, including environmental and genetic factors. Multi-target …

Precise streamflow estimation plays a key role in optimal water resource use, reservoirs
operations, and designing and planning future hydropower projects. Machine learning …

Three active learning schemes are used to generate training data for Gaussian process
interpolation of intermolecular potential energy surfaces. These schemes aim to achieve the …

This paper presents the development of hybrid machine learning models to forecast the
natural flows of water bodies. Five models were considered under the analysis: extreme …

The aim of this article is to show how thevpower of statistics and cheminformatics can be
combined, in R, using two packages: rcdk and cluster. We describe the role of clustering …

Accurate streamflow prediction is essential for efficient water resources management.
Machine learning (ML) models are the tools to meet this need. This paper presents a …

The appearance on the free market of synthetic cannabinoids raised the researchers'
interest in establishing their molecular similarity by QSAR analysis. A rigorous criterion for …

Pharmaceutical manufacturers need to analyse a vast number of products in their daily
activities. Many times, the same product can be registered several times by different systems …

Abstract Machine Learning (ML) techniques are becoming an integral part of rational drug
design and discovery. Data-driven modeling regularly outperforms physics-based models …