Hui Zhang

This study identifies pig xenoantigens reactive to human preformed antibodies using proteomic and glycoproteomic methods, revealing potential targets for improving xenotransplantation.

This study shows that altering glycosylation in human cells changes phosphorylation signaling networks, with engineered cells showing reduced phosphorylation responses and rewired signaling pathways.

SPOTTER enables automated, high-plex spatial proteomics and phosphoproteomics by barcoding proteins on tissue sections, achieving deep coverage with LC-MS/MS.

This study shows that desialylation reduces EGFR phosphorylation and signaling by affecting specific glycoforms and phosphosites, highlighting glycan remodeling as a therapeutic strategy for RTK-driven cancers.

This paper demonstrates that HLA-E-targeting diabodies can induce CD8+ T cell-mediated lysis of HIV-1-infected cells, bypassing limitations of classical MHC class I antigens.

This study develops a high-sensitivity spatial proteomics method, SP-Max, to analyze protein expression changes in pancreatic tissues from normal to cancerous states.

The paper develops an automated sample preparation method (AUTO-SP) for proteomic and PTM analysis, showing high correlation and identification of ubiquitinated peptides in breast cancer PDX models.

TabSyM improves predictive modeling of small, high-dimensional biomedical datasets by generating synthetic data and aligning cross-cohort distributions.

The paper identifies over 12,000 blood proteins using proteomic strategies and develops a database to catalog their detectability and abundance across different conditions.

This study uses single-cell proteomics and RNA-seq to analyze drug-resistant prostate cancer cells, identifying proteomic sub-clusters and gene expression changes linked to morphological and functional traits.

The paper uses proteomics data and machine learning to identify protein signatures distinguishing renal cell carcinomas from normal tissues and different subtypes.

The paper introduces GPnotebook, a glycoproteomic database and toolkit analyzing cancer-associated glycosylation changes using data from CPTAC.

The paper optimizes data-independent acquisition (DIA) mass spectrometry for single-cell proteomics, achieving reliable quantification of proteins and post-translational modifications at sub-nano-gram levels.

The paper introduces EXoO-Tn, a method to map Tn-glycosylation sites in the human proteome, identifying 947 sites from 480 glycoproteins in Jurkat cells.

OmicsX is a web server that integrates and compares multi-omics datasets, offering analysis tools and visualization to identify biological insights.

OmicsOne simplifies multi-omics data analysis by integrating tools for statistical analysis, machine learning, and visualization to associate molecules or pathways with phenotypes.

Omic-Sig uses multi-omics data to identify and visualize kinase-substrate interactions by analyzing differential abundances between case and control samples.

The paper introduces EXoO, a method for site-specific extraction of O-linked glycopeptides, enabling the mapping of over 3,000 O-linked glycosylation sites across human tissues and revealing significant differences between tumor and normal kidney tissues.

MS-PyCloud is an open-source cloud-based pipeline for LC-MS/MS data analysis that provides scalable, reproducible, and efficient processing of proteomics data.

The paper reanalyzes proteomic and phosphoproteomic data to identify a large number of previously unknown N-linked glycopeptides using GPQuest 2.0.