Reaction Representation

Reaction representation focuses on developing effective computational methods to encode chemical reactions for use in machine learning models. Current research emphasizes multimodal approaches combining textual descriptions, molecular structures (SMILES, reaction graphs), and hypergraph representations to capture the complex nature of reactions, employing techniques like graph neural networks and large language models. These improved representations are crucial for tasks such as reaction prediction, mechanism elucidation, and high-throughput screening, ultimately accelerating chemical discovery and synthesis optimization.