Ying Ding

This study identifies a shared proteomic profile in Alzheimer's disease with and without psychosis and a separate molecular signature linked to postsynaptic density disruption.

The paper introduces a supervised learning algorithm for multi-phenotype genomic prediction, showing improved performance in gene expression and DNA methylation analysis and cell type deconvolution.

SECANT improves clustering and annotation of single-cell multi-omics data by integrating surface protein and RNA information with biology-guided semi-supervised learning.

This paper shows a Kalirin mutation enhances RhoA signaling, causing dendritic regression in mice during adolescence, linking it to schizophrenia-like structural impairments.

This study identifies MAP2 phosphorylation changes in schizophrenia, linking them to neuronal structure and synaptic function impairments through phosphoproteomics and transgenic mouse models.

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

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.