Quantitative structure–activity relationship (QSAR) modelling, an approach that was
introduced 60 years ago, is widely used in computer-aided drug design. In recent years …

Machine learning has the potential to provide tremendous value to life sciences by providing
models that aid in the discovery of new molecules and reduce the time for new products to …

Automated synthesis planning is key for efficient generative chemistry. Since reactions of
given reactants may yield different products depending on conditions such as the chemical …

In synthesis planning, it is important to determine suitable reaction conditions such that a
chemical reaction proceeds as intended. Recent research attempts based on machine …

Binary alloy catalysts have the potential to exhibit higher activity than monometallic catalysts
in nitrogen activation reactions. However, owing to the multiple possible combinations of …

Computer-assisted synthesis planning has emerged as a valuable tool for organic synthesis.
Prediction of reaction conditions is crucial for applying the planned synthesis routes …

Here, we present a new method for evaluating questions on chemical reactions in the
context of remote education. This method can be used when binary grading is not sufficient …

Abstract Machine learning has the potential to provide tremendous value to life sciences by
providing models that aid in the discovery of new molecules and reduce the time for new …

Chemical reactivity models are developed to predict chemical reaction outcomes in the form
of classification (success/failure) or regression (product yield) tasks. The vast majority of the …

In this study, we propose and validate a novel Recurrent Neural Network (RNN) model
designed for handling sequential data in voice question-answering systems. In our system …