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Shunfan Li

2 accepted papers

2026

PLA-MGRA: Multi-Granularity and Relation-Aware Learning for Efficient and Generalizable Protein-Ligand Binding Affinity Prediction

AAAI 2026technical

Protein-Ligand Affinity (PLA) prediction quantifies the interaction strength to guide rational drug design. Existing approaches typically analyze interaction at a single granularity and overlook tightly coupled relationships between protein and ligand in both structure and functionality, consequentl

Cited by 0SourcePDFScholar
2026

Spot-Adaptive Structural Rectification for Spatially Resolved Transcriptomics Data Clustering

IJCAI 2026

Spatially resolved transcriptomics integrates gene expression with spatial coordinates to decode tissue microenvironments. Existing methods predominantly utilize graph structures to model relationships between spots. However, their performance is bottlenecked by the reliability of gene feature graph

Cited by 0Scholar