Here, we showcase how our graph neural network (GNN)-based implicit solvent (GNNIS ... for which the prediction diverges from the linear trend. However, the explicit-solvent simulations of compound I1 ...

To classify temporal muscle synergies and quantify connection weights for both self-connections and connections between muscle synergies, we employed a graph neural network. Our results demonstrate ...

Abstract: Graph neural networks (GNNs) are capable of modeling graph data using various types of nodes and edges, and thus can be widely used in the fields of recommender systems and bioinformatics.