Liqing Zhang

TL;DR: This study is a first attempt on mining of GWA data to examine genetic associations between different diseases and shows that Crohn's disease, rheumatoid arthritis, and type 1 diabetes share evidence of genetic associations at all levels of analysis, offering strong molecular support for the current grouping of the diseases.

TL;DR: The effect of quercetin on the growth and genetic expression of three different commensal gut bacteria was documented for the first time and provides insight into the interactions between genetic regulation and growth.

TL;DR: This work proposes DeepMicro, a deep representation learning framework allowing for an effective representation of microbiome profiles that outperforms the current best approaches based on the strain-level marker profile in five different datasets in disease prediction.

TL;DR: A new web-based curation system that supports the annotation and inspection of several key attributes of potential ARGs, including gene name, antibiotic category, resistance mechanism, evidence for mobility and occurrence in clinically-important bacterial strains is proposed.

TL;DR: Results demonstrate that apigenin affects both the growth and gene expression of Enterococcus caccae, at both the single strain and community levels.