Delaram Pouyabahar

The paper integrates multiple datasets to create a comprehensive human liver cell atlas, identifying new cell types and associations with demographic factors.

FLASH-MM improves single-cell differential expression analysis by using a fast linear mixed-effects model that is accurate and efficient.

sciRED improves the interpretation of scRNA-seq factor analysis by removing confounding effects and mapping factors to known covariates, revealing biological signals in multiple datasets.

This study introduces ExoGRU, a machine learning model that predicts small RNA secretion from sequence, identifies key RNA-binding proteins, and develops exoCLIP to map RNA interactomes in extracellular vesicles.

The paper uses single-cell transcriptomics to compare strain-specific differences in myeloid inflammatory potential in healthy rat livers, revealing strain-specific variations in inflammatory signaling pathways.