Nature

Graph-based deep learning approach for high-throughput protein-DNA interaction scoring

Accurately quantifying protein-DNA interactions (PDIs) is critical for understanding biological processes and facilitating drug design. However, the inherent flexibility of nucleic acids limits the ...
Nature

Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library ...
EurekAlert!

Multi-source graph learning may improve drug–target affinity prediction

Figure 1. Overall framework of MIGDTA. GCN: graph convolutional network; GIN: graph isomorphism network; CNN: convolutional neural network; MLP: multi-layer ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...