Summary:
- This article presents a novel computational framework, "scGNN-DTI," designed to predict drug-target interactions (DTIs) by leveraging single-cell RNA sequencing data.
- The study addresses the challenge of heterogeneous drug responses by integrating graph neural networks with transcriptomic profiles to identify cell-specific drug sensitivities.
- The research provides a scalable approach for drug repurposing and precision medicine, offering a robust method to map the complex relationship between pharmacological compounds and individual cell states.