Chengzhen L. Dai

The paper analyzes the genetic and microbiome contributions to blood metabolite variation across 2,049 individuals, finding that over 60% of metabolites are associated with either genetics or the microbiome, with some showing interaction effects.

This paper introduces MicrobiomeCensus, an algorithm to estimate human population size from sewage samples using microbial taxon abundance distributions, showing it outperforms generic algorithms in simulations and field data.

The paper introduces StrainTrack, a method to track bacterial strains in metagenomes and identifies shared strains between twins.

The paper uses longitudinal wastewater sampling to analyze metabolite temporal dynamics across buildings, revealing distinct feature temporal dynamics and enabling building classification.

This study uses genetic and geographic data to analyze migration patterns and population structure in the US, revealing substructure and demographic history among different groups.

The paper assesses gene network connectivity's role in disease heritability using LD score regression and finds that network annotations are enriched but largely explained by regulatory annotations.

This study assesses the public health risk of antibiotic resistance genes in wastewater by combining metagenomic analysis with risk prioritization across multiple countries.