Anjali Seth

This study establishes quality control standards for single-cell proteomics through inter-laboratory benchmarking, identifying software and technical factors affecting data reliability.

The paper optimizes label-free single-cell proteomics workflows to achieve robust quantification of up to 5,000 proteins per Hela cell at 55 samples-per-day throughput.

The paper introduces nanoSPINS, a platform for high-throughput single-cell multiomics that integrates transcriptomic and proteomic profiling from the same cells, demonstrating improved throughput and statistical power.

This study introduces SC-pSILAC, a method to measure protein abundance and turnover in single cells, revealing differentiation-specific dynamics and cell-type markers in human iPSCs.

This study improves single-cell proteomics by increasing protein identification from ~2000 to over 5000 per cell and enhancing throughput and reliability.

The paper introduces nanoSPLITS, a platform for simultaneous transcriptome and proteome profiling of single cells, and demonstrates its application in cell cycle regulation and cell type identification.

This study presents an automated single-cell proteomics workflow that identifies over 4,000 proteins per cell and detects key regulatory proteins in LPS-perturbed THP-1 cells.

The paper introduces an automated sample preparation workflow for laser microdissection guided proteomics, validated on human tonsil tissue with high cell type specificity.