Development of Complemented Comprehensive Networks for Rapid Screening of Repurposable Drugs Applicable to New Emerging Disease Outbreaks

Research on Network Construction and Application of Novel Drug Repositioning Strategies Background During the COVID-19 pandemic, researchers and pharmaceutical companies have been dedicated to developing treatments and vaccines. Drug repositioning, due to its shortcut, is considered a rapid and effective response strategy. Drug repositioning attemp...

Hierarchical Negative Sampling Based Graph Contrastive Learning Approach for Drug-Disease Association Prediction

Research on Drug-Disease Association Prediction Using Graph Contrastive Learning Based on Layered Negative Sampling The prediction of drug-disease associations (RDAs) plays a critical role in unveiling disease treatment strategies and promoting drug repurposing. However, existing methods mainly rely on limited domain-specific knowledge when predict...

Dual-Level Interaction Aware Heterogeneous Graph Neural Network for Medicine Package Recommendation

Research on Medical Package Recommendation Systems: Heterogeneous Graph Neural Network Based on Dual-Level Interaction Awareness With the widespread application of electronic health records (EHRs) in the medical field, how to mine potential and valuable medical knowledge to support clinical decision-making has become an important research direction...

Equivariant 3D Conditional Diffusion Model for Molecular Linker Design

Equivariant 3D Conditional Diffusion Model for Molecular Linker Design

From early drug discovery researchers face a daunting challenge – to find drug-like candidate molecules among approximately 10^60 possible molecular structures. One successful solution is to start from smaller “fragment” molecules, a strategy known as fragment-based drug design (FBDD). In the FBDD process, the first step is to computationally scree...