Yunlong Liu

This study identifies AUD-associated and ethanol-responsive proteins in human cortical organoids and finds candidate biomarkers linked to AUD and ethanol exposure.

This study uses snRNA-seq to analyze gene expression changes in Scn2a-deficient mice, identifying disrupted pathways in neuronal subtypes of the prefrontal cortex.

The paper investigates how EXOSC3 p.G191 variants affect RNA processing by analyzing transcriptomic, proteomic, and structural data in human cell models.

The paper develops and validates polygenic scores for substance use disorders across multiple ancestries, finding clinically relevant performance in European and Latinx populations but not in African populations.

This study validates the palmitoylation cycle as a therapeutic target in NRAS-mutant cancers by showing that inhibiting ABHD17 reduces tumor growth and synergizes with MEK inhibitors.

This study examines how polygenic risk scores for Alcohol Use Disorder affect microglial responses to ethanol exposure in human iPSC-derived microglia.

The paper uses multiomic profiling of the caudate nucleus to identify gene expression and chromatin changes in AUD, linking them to risk genes through QTL analysis.

The paper introduces MpraVAE, a deep generative model that generates and augments regulatory variant data from MPRA, improving prediction performance for regulatory variants in autoimmune diseases.

This study uses single-cell transcriptomics to analyze FGF23 bioactivity and identify novel inflammatory targets in the kidney, revealing interactions between FGF23 and TNF/NF-κB pathways.

MPRAVarDB provides a database and web server to explore the regulatory effects of genetic variants using MPRA data across multiple cell lines and diseases.

This study uses spatial transcriptomics to analyze a spinal ependymoma tumor, revealing cellular heterogeneity and potential developmental hierarchy within the ependymal cell lineage.

The paper identifies functional 3'-UTR variants linked to alcohol use disorder and related traits using MPRA and GWAS integration.

The paper identifies a PLCG2 variant, PLCG2M28L, associated with increased Alzheimer's disease risk and altered microglial phenotypes, while another variant, PLCG2P522R, reduces disease risk in a mouse model.

AIscEA integrates single-cell gene expression and chromatin accessibility data by aligning cell types based on biological consistency, showing improved robustness and accuracy over existing methods.

DEGAS transfers disease information from patients to cells using deep transfer learning, identifying PHF19high myeloma cells linked to progression.

This study shows SARS-CoV-2 genes Nsp6, Nsp8, and M reduce ATP levels in hPSC-CMs, causing apoptosis and dysfunction, and identifies drugs that may counteract these effects.

The paper integrates GWAS data with multi-omics datasets to identify novel genes for alcohol use disorder and link them to neurodegenerative diseases.

This study links SARS-CoV-2 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment through network-based genomics analysis.

WEVar integrates functional scores from multiple methods to predict noncoding regulatory variants, outperforming existing approaches in simulation and empirical studies.

The paper identifies AREG as a critical driver of bleomycin-induced skin fibrosis and shows that targeting the AREG-EGFR-MEK pathway can prevent fibrosis.

This study shows INPP5D expression increases in Alzheimer's disease, particularly in plaque-associated microglia, and suggests it may be a risk factor and therapeutic target.

This study uses single-cell RNA sequencing to define the temporal cellular and molecular changes in the kidney during sepsis, identifying key gene expression shifts and communication failures that mark critical points in the sepsis timeline.

Stepwise modulation of TGFβ, BMP, and FGF signaling in human pluripotent stem cell aggregates generates innervated, pigmented hair-bearing skin organoids that form planar human skin when grafted onto nude mice.

The paper identifies a rare PLCG2 variant that increases Alzheimer's disease risk and shows increased PLCG2 expression correlates with amyloid deposition in AD patients.

This paper shows that Rtr1 prevents premature transcription termination by restricting the NNS-dependent termination pathway and facilitating low-level elongation of noncoding transcripts.

This study uses snRNA-seq to analyze transcriptomes of 16,000 nuclei from human prefrontal cortex in alcoholics and controls, identifying cell type-specific gene expression changes associated with alcohol dependence.

ICTD improves tissue microenvironment analysis by enhancing cell type identification, marker gene discovery, and functional inference through a semi-supervised deconvolution approach.

The paper identifies functional variants in human brains with alcohol use disorders by combining allele-specific expression analysis with high-throughput reporter assays.

The paper identifies 129 differentially expressed genes in the PFC of alcoholics and links them to pathways and modules associated with alcohol dependence and consumption.

The paper develops regSNPs-intron, a random forest classifier to prioritize intronic SNVs for disease, validated using ASSET-seq functional assays.