Liangyun Zhang

scRGP predicts single-cell genetic perturbation transcriptional responses using rank-based deep learning, improving performance over existing methods for single, double, and cross-cell-line perturbations.

This study uses a Transformer model to design novel succinate dehydrogenase inhibitors against agricultural fungi, resulting in potent antifungal compounds through virtual screening and optimization.

AIPAMPDS designs and screens antimicrobial peptides using AI, identifying 10 lead peptides with high antimicrobial activity and low hemolysis.

NcPath integrates and visualizes miRNA and lncRNA interactions with KEGG pathways, enabling enrichment analysis of non-coding RNA involvement in biological processes.

Deep6mA is a deep learning framework for identifying DNA 6mA sites, achieving high accuracy across species and revealing conserved sequence patterns and regulatory roles of 6mA.