All Outputs (2)

HCat-GNet: a Human-Interpretable GNN Tool for Ligand Optimization in Asymmetric Catalysis (2025)
Journal Article
Aguilar-Bejarano, E., Özcan, E., Rit, R. K., Li, H., Lam, H. W., Moore, J. C., Woodward, S., & Figueredo, G. (2025). HCat-GNet: a Human-Interpretable GNN Tool for Ligand Optimization in Asymmetric Catalysis. iScience, Article 111881. https://doi.org/10.1016/j.isci.2025.111881

Optimization of metal-ligand asymmetric catalysts is usually done by empirical trials, where the ligand is arbitrary modified, and the new catalyst is re-evaluated in the lab. This procedure is not efficient and alternative strategies are highly desi... Read More about HCat-GNet: a Human-Interpretable GNN Tool for Ligand Optimization in Asymmetric Catalysis.

Data Checking of Asymmetric Catalysis Literature Using a Graph Neural Network Approach (2025)
Journal Article
Aguilar-Bejarano, E., Deorukhkar, V., & Woodward, S. (2025). Data Checking of Asymmetric Catalysis Literature Using a Graph Neural Network Approach. Molecules, 30(2), Article 355. https://doi.org/10.3390/molecules30020355

The range of chemical databases available has dramatically increased in recent years, but the reliability and quality of their data are often negatively affected by human-error fidelity. The size of chemical databases can make manual data curation/ch... Read More about Data Checking of Asymmetric Catalysis Literature Using a Graph Neural Network Approach.