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Found 6 papers, 2 papers with code
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking
Predicting the docking between proteins and ligands is a crucial and challenging task for drug discovery.
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network
The proposed ELGN firstly adds a super node to the 3D complex, and then builds a line graph based on the 3D complex.
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction
In this paper, we propose a novel end-to-end graph generation model for retrosynthesis prediction, which sequentially identifies the reaction center, generates the synthons, and adds motifs to the synthons to generate reactants.
Recent Advances in Network-based Methods for Disease Gene Prediction
Thirdly, an empirical analysis is conducted to evaluate the performance of the selected methods across seven diseases.
Semantic Hierarchy Preserving Deep Hashing for Large-scale Image Retrieval
Deep hashing models have been proposed as an efficient method for large-scale similarity search.
Microbial community pattern detection in human body habitats via ensemble clustering framework
To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data.
