Zhe Sun

BREM-SC is a Bayesian model that jointly clusters single-cell transcriptomic and proteomic data, improving accuracy and quantifying clustering uncertainty.

The paper introduces MTDsite, a multi-task deep learning method for predicting protein-binding residues across DNA, RNA, peptide, and carbohydrate, achieving higher accuracy than existing methods.

This study identifies synaptic proteome alterations in the primary auditory cortex of schizophrenia patients, showing coordinated changes in postsynaptic proteins not explained by global protein levels or confounding factors.

BAMM-SC clusters droplet-based scRNA-seq data from multiple individuals by accounting for batch effects and heterogeneity, improving accuracy over existing methods.