1 citations · 1 across the 3 of their papers we have counts for
4 papers
Learning Mechanistic Reasoning for Chemical Reactions with Large Language Models
Xingyu Dang, Haocheng Tang, Junmei Wang +1
Reaction mechanisms consist of the step-by-step sequences of elementary reactions that explain chemical transformations. Learning the mechanism logic is therefore essential for enh…
Apo2Mol: 3D Molecule Generation via Dynamic Pocket-Aware Diffusion Models
Xinzhe Zheng, Shiyu Jiang, Gustavo Seabra +2
Deep generative models are rapidly advancing structure-based drug design, offering substantial promise for generating small molecule ligands that bind to specific protein targets.…
DecoyDB: A Dataset for Graph Contrastive Learning in Protein-Ligand Binding Affinity Prediction
Yupu Zhang, Zelin Xu, Tingsong Xiao +4
Predicting the binding affinity of protein-ligand complexes plays a vital role in drug discovery. Unfortunately, progress has been hindered by the lack of large-scale and high-qual…
Morphological Profiling for Drug Discovery in the Era of Deep Learning
Qiaosi Tang, Ranjala Ratnayake, Gustavo Seabra +9
Morphological profiling is a valuable tool in phenotypic drug discovery. The advent of high-throughput automated imaging has enabled the capturing of a wide range of morphological…