L. Liang

This study identifies subtype-specific influenza A virus-host protein interactions that correlate with different pathogenic outcomes.

This study uses single-cell RNA-seq to analyze human infant retina, identifying cell types, communication networks, and developmental changes, providing a resource for retinal research and regenerative medicine.

This study uses single-cell RNA sequencing to analyze the cellular diversity and molecular markers in the retina of a trisomy 21 fetus, revealing communication networks and novel markers.

This paper shows that transmural mean hoop stress of the aortic wall can be calculated from in vivo images using thin-walled models without needing patient-specific material properties or residual deformations.

This paper develops a machine learning approach to estimate aortic wall constitutive parameters from 3D geometries at different blood pressure levels, improving efficiency over traditional inverse methods.

The paper analyzes the evolution and adaptation of H7N9 influenza viruses in China, identifying lineage-specific mutations and high-pathogenicity strains.

This study uses deep learning to estimate collagenous tissue mechanical properties from microscopy images with high accuracy.