Rui Sun

The paper presents a comprehensive spatial proteome map of human tissues and cancers, enabling drug response analysis and target discovery.

This study identifies two molecular subtypes of thyroid cancer using multi-omics data, showing distinct prognostic and therapeutic implications.

The paper develops a foundation model using perturbation proteomics data to predict drug responses and improve breast cancer prognosis.

Integral-Oms enables sequential extraction and profiling of multiple omics layers from biopsy tissue, revealing suppressed ferroptosis in colorectal cancer tissues.

GeoAB improves antibody design by generating realistic CDR structures and enabling accurate affinity maturation through mutation effect prediction.

BatchServer provides a web platform for evaluating, visualizing, and correcting batch effects in omics data using autoComBat, PVCA, and UMAP.

The paper investigates how genomic alterations affect molecular networks in prostate cancer by integrating genomic, transcriptomic, and proteomic data from 105 samples, identifying a sub-network predictive of tumor aggressiveness and recurrence.

This paper presents a computational strategy to optimize spectral library size for DIA-MS data, improving peptide and protein identification rates in colorectal and carcinoma samples.

The paper introduces DPHL, a pan-human protein mass spectrometry library built using DIA and PRM, and demonstrates its utility in identifying differentially expressed proteins in prostate cancer and DLBCL.