The current global health threat by the novel coronavirus disease 2019 (COVID-19) requires
an urgent deployment of advanced therapeutic options available. The role of …

Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

We present SMILES-embeddings derived from the internal encoder state of a Transformer
[1] model trained to canonize SMILES as a Seq2Seq problem. Using a CharNN [2] …

This review presents the main aspects related to pharmacokinetic properties, which are
essential for the efficacy and safety of drugs. This topic is very important because the …

This is a book on data analysis with a specific focus on the practice of predictive modeling.
The term predictive modeling may stir associations such as machine learning, pattern …

Benzo [a] pyrene is a known carcinogen, which derives from fossil fuel combustion, cigarette
smoke, and generic biomass combustion including traffic emissions. This potent carcinogen …

Successful deep learning critically depends on the representation of the learned objects.
Recent state-of-the-art pharmaceutical deep learning models successfully exploit graph …

Efficient and accurate prediction of molecular properties, such as lipophilicity and solubility,
is highly desirable for rational compound design in chemical and pharmaceutical industries …

Introduction: Although significant progress has been made in high-throughput screening of
absorption, distribution, metabolism and excretion, and toxicity (ADME-Tox) properties in …

Abstract The Online Chemical Modeling Environment is a web-based platform that aims to
automate and simplify the typical steps required for QSAR modeling. The platform consists of …