The drug discovery process is hugely data-intensive, making it an ideal application for artificial intelligence (AI) and machine learning. But it isn’t as straightforward as it sounds. Gaining valuable insight can be complex. Database pioneer Emil Eifrem of Neo4j explains why graph software could be the missing link in better understanding data so that the power of AI can put it into context, and pull out the most salient information for drug discovery researchers.
Read more: https://www.jforcs.com/are-graph-databases-the-key-ingredient-ai-is-missing-in-drug-discovery/
Keywords: drug discovery • Graph Data