One of the most stubborn obstacles in computational drug discovery is the cold-start problem: how do you predict whether a new drug will interact with a protein target when the model has never seen a ...

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...