Jaeyun Sung

The paper introduces a disease-agnostic Nasal Microbiome Wellness Index (NMWI) that quantitatively assesses nasal microbiome health using 16S rRNA gene data, outperforming traditional diversity indices in distinguishing healthy from non-healthy samples.

This study identifies unique proteomic signatures in melanoma-derived lymphatic exosomes that contribute to premetastatic niche formation in sentinel lymph nodes.

LAMPP provides a standardized benchmark for evaluating host phenotype prediction from gut metagenomic data, showing that traditional methods remain competitive.

The paper identifies UDP-P2Y6 signaling as a key driver of microglial calcium activity, phagocytosis, and neuroinflammation during epileptogenesis.

The paper introduces GMWI2, a gut microbiome health index that improves disease prediction accuracy compared to previous models and traditional diversity indices.

TaxiBGC improves BGC prediction in metagenomes by using taxonomy-guided methods, showing better performance than read-based approaches and linking BGCs to human diseases.

The paper introduces GMHI-webtool, an online tool that computes and visualizes gut microbiome health indices from stool metagenomic data, enabling easier interpretation and comparison with reference datasets.

The paper introduces a gut microbiome health index (GMHI) that predicts general health status using species-level profiling and validates its robustness across multiple datasets.

The paper uses mass cytometry to analyze immune cell subsets in PBC patients and controls, identifying differences in cell abundance associated with disease and disease stage.