Alexander M. Morin

This study evaluates coexpression analysis methods in single-cell and bulk data, finding that xCell provides more replicable and biologically interpretable results than other modes.

The paper identifies reproducible transcription regulator coexpression patterns using single-cell RNA-seq data across human and mouse, showing consistency with ChIP-seq results.

The paper develops a computational simulator to study how intracellular regulatory signals propagate from single cells to bulk tissue expression data, finding that such propagation is rare and conditions are highly specific.

The paper integrates ChIP-seq and TR perturbation data to rank human and mouse TR-target interactions and identify orthologous relationships.

This study curates experimentally verified transcriptional regulatory interactions from literature to build a high-confidence resource for gene regulatory network development.

The paper examines DNA methylation differences in white blood cell types between newborn and adult blood, showing how these changes reflect immune maturation and affect cell type prediction accuracy.