Shaoline Sheppard

The paper uses single-cell transcriptomics and neural network classifiers to identify B cell signaling as critical for NK cell expansion in allogenic therapy.

This study shows that SCAN domain zinc-finger proteins bind transposon sequences and anchor nucleosomes, affecting chromatin structure and regulatory states.

This study identifies ZNF274's role in anchoring lineage-specific gene clusters within repressive perinucleolar compartments, revealing its impact on chromatin structure and gene regulation.

The paper creates a large single-cell endometrial atlas and uses AI to identify gene expression and receptor-ligand changes associated with endometriosis, developing predictive models for disease severity.

The paper quantifies TE-mediated cis-regulation using statistical learning, showing TE-embedded CREs influence gene expression and can be predicted from RNA-seq data.

The paper develops a machine learning framework to estimate cell subtype-specific drug sensitivity from bulk data, applying it to leukemia datasets to identify potential therapeutic targets.

The paper identifies a dynamic TE-embedded miRNA expression landscape in human brain development and introduces a web tool for exploring these dynamics.

The paper identifies KZFP:TE transcriptional profiles and TE-derived promoters in the developing human brain, showing their role in neurogenesis.