Wenyu Zhou

The paper examines gut microbiome changes in chronic systolic heart failure patients, linking microbiome alterations to disease severity and clinical improvement.

The paper identifies CeD-specific TCRs in peripheral blood that classify celiac disease independently of gluten intake, showing higher predictive power than traditional TCRs.

The paper maps T-cell receptor β sequences to specific HLA allotypes using population-level TCR repertoire data, enabling accurate HLA imputation and revealing insights into TCR-HLA interactions.

The paper identifies public TCRB sequences expanded in CD or UC, associated with HLA alleles and antigen-specific immune responses, showing differential expansion in CD compared to UC and healthy controls.

Seq2MAIT identifies MAIT cells from bulk TCR-sequencing data using a transformer-based model, achieving AUROC >0.80 across datasets.

This study tracks microbiome changes across four body sites in 86 participants over six years, revealing site-specific stability, individualized dynamics, and altered patterns in insulin-resistant individuals.

This paper introduces a statistical method to identify time intervals of temporal omics biomarkers in longitudinal studies, showing high specificity and sensitivity across simulated and real datasets.

iNetModels 2.0 provides an interactive platform for visualizing and exploring multi-omics associations in human health and disease.

The paper assembles the pig-tailed macaque genome using linked-read sequencing and HiC scaffolding, achieving chromosome-level resolution and identifying large-scale chromosomal rearrangements with humans.

The paper characterizes the dynamic multi-omic molecular response to acute exercise and identifies biomarkers of fitness.

DIAlignR improves retention time alignment in SWATH-MS data by aligning raw MS2 chromatograms, outperforming existing methods and reducing alignment error significantly.

The paper assesses exome sequencing in a healthy cohort to determine the frequency of medically actionable and non-actionable findings, finding 17% had actionable variants, including some outside standard guidelines.