3 papers
cs.LG2026
ChemHyperMag: Physics-informed magnetic hypergraph learning improves molecular ADMET prediction
Hexiao Ding, Hongzhao Chen, Jing Lan +12
Accurate prediction of ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) is important for drug discovery. Most predictors use undirected molecular graphs and pa…
cs.LG2026
Structure-Aware Contrastive Learning with Fine-Grained Binding Representations for Drug Discovery
Jing Lan, Hexiao Ding, Hongzhao Chen +8
Accurate identification of drug-target interactions (DTI) remains a central challenge in computational pharmacology, where sequence-based methods offer scalability. This work intro…
cs.CV2026
DeepMoLM: Leveraging Visual and Geometric Structural Information for Molecule-Text Modeling
Jing Lan, Hexiao Ding, Hongzhao Chen +8
AI models for drug discovery and chemical literature mining must interpret molecular images and generate outputs consistent with 3D geometry and stereochemistry. Most molecular lan…