This is the repo for the paper "Tensor Databases Empower AI for Science: A Case Study on Retrosynthetic Analysis"
Tensor database; Approximate retrieval; Retrosynthetic
- We design and implement the first tensor database system.
- We design a tensor format for storing chemical reactions. This format efficiently stores all key information related to chemical reactions, including reactants, products, and reaction conditions (such as solvents and reagents). We provide users with services for storing and retrieving chemical reactions.
- We integrate multiple retrosynthetic analysis prediction models including reactants prediction and reaction conditions prediction. We also integrate SMILES embedding models. These integrations offer full-cycle retrosynthetic analysis services to users. Our work reduces usage costs and improves the pipeline's efficiency.
- We provide search and analysis functions. Through these interfaces, we re-rank and analyze the final prediction results. At the same time, we provide real reaction equations similar to the predicted results for user reference. These works can enhance the accuracy and interpretability of the final outcomes.