Guoqing Zhang

This paper benchmarks confounder-aware differential abundance methods for microbiome studies, finding that covariate adjustment improves false discovery control but reduces sensitivity, with different strategies performing better under various conditions.

SheepEpimap combines 516 histone CUT&Tag, ATAC-seq and RNA-seq datasets from 43 sheep tissues to annotate 2.93 million cis-regulatory elements and 145,407 allele-specific variants for trait interpretation.

IBDkb integrates multi-source IBD data with AI tools to enhance research and drug discovery by enabling efficient exploration of drug-target-trial associations.

This study investigates antibiotic resistance genes and bacteria in hadal trench sediments using cultivation and metagenomics, finding a pristine reservoir with distinct ARG dynamics and phylogenetic clusters.

The paper introduces xAI-MTBDR, an AI framework that identifies drug resistance mutations in MTB and predicts resistance, outperforming existing methods and revealing new resistance markers.

The paper presents a multi-tissue sheep atlas identifying regulatory variants and their effects on molecular phenotypes, revealing allelic heterogeneity and evolutionary patterns.

The paper introduces StCEL, a method for detecting and sequencing native sialoglycoRNA, showing its upregulation in cancers and correlation with poor prognosis.

PreDigs provides a database of context-specific cell-type markers and subtypes for digestive system cell annotation, offering tools for single-cell classification and analysis of over 3.4 million cells.

This study introduces LEAP, a method for estimating shared proteomic architectures across traits, finding 585 significant proteomic correlations among 50 traits using UK Biobank data.

DeepSeMS uses a large language model to predict chemical structures of secondary metabolites from microbial gene clusters, outperforming existing methods and discovering novel compounds in the ocean microbiome.

The paper identifies novel structural variants in Han Chinese genomes using long-read sequencing and links them to phenotypic diversity and disease susceptibility.

This study identifies region-specific and subtype-specific genes in mouse forebrain cholinergic neurons using spatial multi-omics, revealing low mRNA-protein correlation and functional similarity.

The paper introduces LAMAR, a transformer-based foundation language model for RNA regulation, which outperforms state-of-the-art methods in predicting mRNA translation efficiency and half-life.

This study shows that removing duplicate reads improves metagenomic assembly and binning yields and reduces computational costs in complex environmental samples.

FunGeneTyper is a deep learning framework for ultra-accurate classification and discovery of functional genes in microbiomes, outperforming existing methods in multiple environments.

dbDEMC 3.0 updates a database of differentially expressed miRNAs in human and model organism cancers, expanding data entries and integrating functional annotations.

The paper introduces Coronavirus GenBrowser (CGB), a tool for analyzing and visualizing SARS-CoV-2 genomic sequences to study transmission and evolution.

This study develops a drug repositioning platform by integrating anti-fibrosis knowledge and machine learning models to identify potential drugs for fibrosis treatment.