Saad Khan

The paper uses single-cell proteomics and transcriptomics to reveal cell-type-specific functional coordination in PBMCs, showing protein covariation that reflects protein-protein interactions and pathway rewiring.

The paper shows proteomic asymmetry in mouse and human embryos that influences lineage segregation.

The paper quantifies proteomes and RNA levels in human testis cells to infer post-transcriptional regulation using a Bayesian model called BayesPG.

The paper introduces nPOP, a method for preparing single-cell samples for multiplexed proteomics, achieving accurate quantification of thousands of proteins per cell.

The paper identifies regulators of nucleocytoplasmic protein transport in macrophages using single-nucleus proteomics and validates findings through knockdown experiments.

The paper quantifies protein covariation in single human cells during EMT, revealing dynamic protein-protein correlations that reflect biological regulation masked by cluster-average dynamics.

The paper introduces nPOP, a method for single-cell protein covariation analysis, revealing cell cycle dynamics and functional differences between melanoma subpopulations.

Multiplexing nonisobaric isotopologous mass tags (mTRAQ) with data-independent acquisition and DIA-NN increases sensitive proteomics throughput 3-fold while cutting missing data below 3% in bulk and single cells.