Chan Wang

This study shows that IFNγ-driven inflammation in the nasal mucosa increases influenza virus shedding and transmission, linking infectiousness to host immune responses rather than viral replication alone.

LongStrain improves strain-level analysis in longitudinal metagenomic data by jointly modeling strain proportions and genomic variants, outperforming existing methods in variant calling and proportion estimation.

ARZIMM infers microbial interactions and community stability from longitudinal microbiome data using a zero-inflated mixed-effects model.

The paper introduces a microbial trend analysis framework to characterize dynamic microbial patterns in longitudinal studies, showing its effectiveness in trend detection, group comparison, and classification.

The paper introduces JointMM, a joint modeling framework for analyzing longitudinal microbiome proportions and time-to-event data, showing its effectiveness in identifying microbial associations with disease progression.

The paper introduces a causal mediation model for high-dimensional microbiome data to estimate and test microbial causal effects in a three-factor study design.