Liangliang Zhang

This paper introduces PGL, a Bayesian regression method for microbiome feature selection that uses phylogenetic trees to improve detection of exposure-associated ASVs.

The paper evaluates common beta diversity metrics in microbiome analysis, identifies their mathematical shortcomings, and introduces a classification framework with tools to improve their validity.

BayCT detects circadian biomarkers and estimates molecular circadian time in human brain transcriptomes, outperforming existing methods by jointly addressing both tasks.

This study shows that a Muc2 mutation in Winnie mice leads to colitis-associated tumorigenesis driven by the gut microbiome and metabolome, with SPF conditions promoting severe disease and CAC.

This paper introduces an EHR foundation model integrating Polygenic Risk Scores to improve disease prediction and personalized healthcare using All of Us data.

magpie evaluates statistical power for differential RNA methylation analysis in m6A sequencing by simulating data and assessing factors like sample size and effect size.