Xiaowei Zhan

The paper identifies a urinary metabolomic signature linked to small intestinal bacterial overgrowth in children with short bowel syndrome using gas chromatography/mass spectrometry.

This paper introduces a supervised contrastive learning framework for multi-omics prediction models, showing improved accuracy over single-omics approaches in type 2 diabetes and high-fat diet studies.

GPSNorm fits slide, spatial technical and biological effects in one Bayesian negative binomial model, carrying normalization uncertainty into differential expression and lowering log-fold change error in simulations.

This paper introduces ORBIT, an oligonucleotide-based genetic toolkit for Pseudomonas aeruginosa that enables rapid, precise, and high-throughput hypomorph screening of essential genes.

This study identifies TDCA, a microbiota-derived bile acid, as a mediator that restores immune checkpoint therapy efficacy after antibiotic-induced hyporesponsiveness by enhancing CD8+ T cell antitumor immunity.

This study shows that the time of day affects cancer immunotherapy efficacy through a circadian clock-dependent chemokine axis in mice.

The paper introduces THNet, a method to analyze HLA-TCR cross-reactivity, revealing new disease associations and improving transplantation outcomes.

The paper integrates proteomics data from Olink and SomaScan to identify pQTLs and develop a resource for transcriptome and proteome-wide association studies, with applications to inflammatory bowel disease.

This study evaluates machine learning algorithms and feature selection stability in multi-omics microbiome datasets, finding that nonlinear models and multi-omics integration improve predictive performance and reproducibility.

This study identifies 63 AMD risk loci across multiple ancestries, highlighting ancestry-dependent genetic heterogeneity and potential therapeutic targets.

The paper analyzes WGS data of E. coli isolates to show that blaTEM gene amplification correlates with resistance to AMC and TZP but not SAM, highlighting the need for comprehensive analysis of genetic determinants in BL/BLI resistance.

ScopeViewer provides a browser-based tool for visualizing spatial transcriptomics data with features for interactive exploration, dual viewing, optimized bandwidth, and data security.

STAr provides an integrated platform with curated datasets and methods to evaluate and develop spatial transcriptomics analysis tools.

IsoAnalytics provides a user-friendly web server for analyzing and visualizing single-cell proteomics data from the Isoplexis platform, accessible to non-experts.

MB-SupCon integrates microbiome and metabolomics data to improve prediction accuracy in microbiome-only datasets, achieving high accuracy in predicting insulin resistance, sex, and race.

This study identifies mobile genetic elements driving β-lactamase gene amplification in non-CP-CRE bloodstream infections through genomic analysis.

The paper develops KIRCLE to genotype KIR genes from whole exome sequencing data and analyzes its associations with HLA alleles and clinical traits in TCGA and UK Biobank.

MetaPrism enables joint analysis of taxa and gene abundances in metagenomic data to identify potential biomarkers for therapeutic response prediction.

MB-GAN generates synthetic microbiome data that mimic real datasets, preserving key statistical properties for method development.

HiddenVis visualizes and interprets deep learning models for time series data using accelerometer data from NHANES to identify activity patterns linked to mortality.

HARMONIES infers sparse microbiome networks using a zero-inflated negative binomial model and regularization, outperforming existing methods and identifying disease-associated microbial communities.

VAMPr predicts antibiotic resistance using genomic data by analyzing variant associations and building machine learning models.

The paper develops a deep learning tool to analyze pathology images and identify TME features predictive of survival in lung cancer.

This paper develops SClineger, a Bayesian model to correct genetic drop-outs in scRNA-Seq data for accurate lineage tracing across tissues and time scales.

This study identifies circE7, a circular RNA from HPV that is translated into E7 oncoprotein, contributing to cervical cancer progression.

The paper analyzes rare coding variants in smoking and drinking behavior using exome chip data, finding that they contribute to phenotypic variation but require larger samples for individual variant associations.

The paper identifies cancer-associated T cells using TCR repertoire and gene expression data, revealing novel regulators and antigens with potential for immune monitoring and immunotherapy.

The paper develops methods to analyze multi-allelic variants in large sequence datasets, showing improved power and unbiased estimates in association tests.