A5044390010- Advanced Graph Neural Networks
- Machine Learning in Materials Science
- Computational Drug Discovery Methods
- Genetics, Bioinformatics, and Biomedical Research
- SARS-CoV-2 and COVID-19 Research
- Cell Image Analysis Techniques
East China University of Science and Technology
2021
Graph neural networks (GNNs) constitute a class of deep learning methods for graph data. They have wide applications in chemistry and biology, such as molecular property prediction, reaction drug-target interaction prediction. Despite the interest, GNN-based modeling is challenging it requires data preprocessing addition to programming learning. Here, we present Deep Library (DGL)-LifeSci, an open-source package on graphs life science. (DGL)-LifeSci python toolkit based RDKit, PyTorch,...
Abstract In this information era, there is an urgent need for tighter integration of bioinformatics and experimental biology. The enormous amount data generated by biological experiments calls extensive computational analysis. Many textbooks at present mainly focus on theories, which hinders the vigorous development scientific research. As a result, most students are simply familiar with theories but lack opportunity to put them into practice. Here, we our docking project conducted during...