Dong Soo Lee

STopover analyzes spatial transcriptomics data to identify cell-cell interactions and colocalization patterns in the tumor microenvironment.

The paper quantifies the lymphatic drainage of cerebrospinal fluid in mice using 64Cu-labeled bacterial extracellular vesicles and identifies cervical lymph nodes as the primary drainage sites.

The paper uses spatial transcriptomics to analyze brain cell changes in mouse dementia models after immunomodulation treatments and develops a new analysis tool.

The paper uses [64Cu]Cu-albumin PET to quantify age-related decline in CSF-lymphatic efflux in mice, showing slower clearance and reduced lymph node activity in aged mice.

The paper uses k-core percolation on dynamic resting-state fMRI to reveal time-varying hierarchical brain connectivity and its relation to mental states.

spSeudoMap maps cell types from spatial transcriptomics data using unmatched single-cell RNA-seq data by creating virtual cell mixtures and domain adaptation.

CellDART adapts neural networks to infer cell type spatial distribution from single-cell and spatial transcriptomic data, showing effectiveness in human and mouse tissues.

This paper embeds functional brain networks from resting-state fMRI into hyperbolic space to visualize and detect anomalies in autism spectrum disorder.

The paper identifies characteristic core structures in resting-state fMRI data using hyperbolic disc embedding and k-core percolation, revealing individual differences in brain connectivity patterns.

This study characterizes spatiotemporal glial cell activation in an Alzheimer's disease model, revealing early white matter changes and later gray matter involvement.

The paper introduces SPADE, a method that integrates spatial transcriptomic data with deep learning features from tissue images to identify genes associated with morphological contexts.

The paper investigates the mutational impact of ionizing radiation on normal cells and confirms these signatures in IR-induced cancers.

This study shows that focused ultrasound with microbubbles improves beta-amyloid drainage in Alzheimer's model mice by enhancing brain-to-cerebrospinal fluid clearance.

The study links disease-associated microglia enrichment to neuronal subtype reconfiguration, particularly in cortical layer 4 excitatory neurons, in Alzheimer's disease.

The paper predicts age-related brain metabolic changes using a variational autoencoder and shows APOE4 status significantly affects metabolic degeneration in specific brain regions.

The paper introduces G-FISH, a method for RNA detection in FFPE tissues, and demonstrates its ability to detect specific RNAs in mouse brain and tumor tissues with high sensitivity and low background.