Editorial Deep Learning and Graph Embeddings for Network Biology

This special issue contains a multitude of high-quality manuscripts that cover a broad range of applications supporting the need to discuss and foster these advances in a systematic way, provide practical tools for practitioners, and describe new techniques that can facilitate biomedical discovery. We received 24 manuscripts and after peer review only 9 manuscripts were accepted. Manuscripts came from all the world (US, Italy, Australia, China) and covered both theoretical (e.g., development of novel methods) and practical (e.g., data integration or predicting metabolite associations) considerations of biological network analysis. The use of graph neural networks (GNNs) for prediction of biological associations has had a significant impact in this special issue.