Seyun Oh

The paper uses spatial transcriptomics to analyze molecular differences in mood disorders and biological sex in the human prefrontal cortex, identifying sex- and disorder-specific gene expression patterns.

SynAPSeg provides a framework and dataset for deep learning-based synapse detection and quantification, achieving expert-level performance and revealing age-related synaptic changes.

This study maps molecular and genetic signatures of schizophrenia in human prefrontal cortex across spatial scales, revealing altered BDNF-TrkB signaling and inhibitory circuit dysfunction.

The paper performs snRNA-seq on human lateral septum tissue to identify cell types and marker genes, finding conserved and species-specific expression patterns.

This study investigates TrkB signaling in the lateral septum using RNA-seq, identifying gene expression changes linked to psychiatric and neurodegenerative disorders.