Megan Lynn Stanifer

SEHI-PPI predicts human-influenza protein-protein interactions using a double-view deep learning framework with adaptive negative sampling, outperforming existing methods and demonstrating strong generalizability.

This study uses time-resolved RNA sequencing and mathematical modeling to analyze SARS-CoV-2 host cell interactions, revealing transcriptional dynamics and identifying druggable host pathways.

The paper identifies a Neandertal introgressed haplotype in the OAS1 gene associated with increased risk of severe COVID-19 and shows it impairs SARS-CoV-2 clearance through genetic regulation of OAS1 expression.

This study uses single-cell RNA-seq data to analyze how SARS-CoV-2 infection alters intestinal epithelial-immune cell interactions and identifies potential drug targets and repurposing strategies for COVID-19.

The paper uses single-cell RNA-Seq and imaging to study how intestinal cell types respond to viral infection, finding that each lineage has unique antiviral responses.

The paper identifies a novel primate-specific ACE2 isoform, dACE2, which is an interferon-stimulated gene but not functional for SARS-CoV-2 entry.

This study identifies miRNA-320a as a hypoxia-regulated factor that promotes barrier formation in human intestinal epithelial cells through HIF-dependent mechanisms.