Chuanxi Huang

This study develops a high-throughput single-cell proteomics workflow combining nPOP with quantitative hyperplexing, achieving high sensitivity and quantification across multiple cell types.

The paper introduces SWIFT, a fast and efficient proteomic workflow for processing microgram-level FF and FFPE tissues, achieving high repeatability and deep proteome coverage.

The paper introduces an automated system for high-throughput proteomic data generation, demonstrating its robustness and application in spatial proteomics and plasma/cell line profiling.

This paper introduces Integral-Hyperplex, a method combining isobaric tags and tandem mass tags to increase single-cell proteomics throughput by 30-fold, validated through quantification experiments and automated labeling.

This paper introduces a simple one-step vial-based pretreatment method for deep single-cell proteomics and applies it to study oocyte aging, identifying age-related protein markers.