Nature

Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting

We investigate the potential of graph neural networks (GNNs) for transfer learning and improved molecular property prediction in the context of funnels or screening cascades characteristic of drug ...
Nature

Heterogeneous graph neural networks reveal molecular mechanisms of folate deficiency in placental insufficiency through multiomics integration

Placental insufficiency stands as a severe pathological state during gestation that plays a substantial role in triggering adverse outcomes for both mother and developing fetus—outcomes that encompass ...
EurekAlert!

Molecular merged hypergraph neural network for explainable solvation Gibbs free energy prediction

Background: Molecular interactions are central to numerous challenges in chemistry and the life sciences. Whether in solute–solvent dissolution, adverse drug–drug interactions, or protein complex ...