Feixiong Cheng

This study identifies OASL as an inhibitor of ADAR1 p150, showing it limits RNA binding and A-to-I editing while modulating antiviral immunity.

DrugLM enhances drug-target interaction predictions by integrating textual embeddings from large language models into DTI models, showing strong performance without fine-tuning.

This study shows GABA receptor B signaling promotes GBM growth in females through immune mechanisms, with sex-specific effects on survival and treatment outcomes.

This study develops triazole-based WDR5 inhibitors that show improved brain penetration and antiproliferative activity against glioblastoma CSCs, with synergistic effects when combined with ATAD2 inhibitors.

The paper develops a neuron-specific interactome map in human excitatory neurons to identify novel risk genes and pathways in Alzheimer's disease.

This study investigates how dietary fatty acids interact with gut microbiota and host metabolism to influence lipid homeostasis and cardiometabolic disease in mice.

This study develops a single-cell digital twin framework to identify drug targets and repurposable medicines in Alzheimer's disease using single-nuclei RNA-seq and ATAC-seq data.

This study shows that SARS-CoV-2 deISGylation by PLpro suppresses innate immunity and promotes viral replication by modulating cellular metabolism.

The paper identifies cell-type-specific metabolic regulators in Alzheimer's disease using scFUMES, revealing key interactions that reduce pathological tau species.

The paper uses a Bayesian model to identify shared genetic components across complex diseases, finding potential drug targets with lower side effects and repurposing opportunities.

This study integrates multi-omics data using network medicine to identify potential drug targets and repurposable treatments for ALS.

This study combines APOE4 and TREM2R47H in female tauopathy mice to identify pathways activated by AD risk factors, finding cGAS-STING signaling and microglial senescence as potential drivers.

This paper presents an explainable AI framework using molecular images to identify novel antibiotic candidates from FDA-approved drugs.

The paper uses molecular dynamics simulations to analyze four SCN2A variants, revealing how they affect channel structure and function, with R937C being the most unstable.

The paper introduces PIONEER, a deep learning framework for predicting protein-protein interfaces, and shows disease mutations are enriched in these interfaces, identifying oncoPPIs linked to cancer survival and drug responses.

This study identifies GPCR targets of gut microbiota metabolites in Alzheimer's disease using multi-omics and machine learning.

The paper uses single-cell multi-omics data to predict gene regulatory networks in Alzheimer's disease and control, identifying cell-type-specific dysregulation and potential drug targets.

This study examines the relationship between sTREM2 and inflammatory activity in early stage Alzheimer's disease using clinical and biomarker-defined groups.

SOAR provides a curated spatial transcriptomics database and analysis tools to facilitate disease mechanism studies and drug discovery.

This paper introduces a network-based deep learning framework to translate GWAS findings into biological insights and drug targets for Alzheimer's disease, identifying 156 putative risk genes.

This study uses network-based methods to identify and validate metformin as a potential treatment for atrial fibrillation using human-derived atrial-like cardiomyocytes.

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

AlzGPS integrates multi-omics data and networks to identify repurposable drugs for Alzheimer's disease.

The paper examines sex differences in COVID-19 outcomes and immune responses using single-cell RNA-sequencing and clinical data, finding higher risk for males and potential mechanisms for sex-specific treatments.

This study identifies disease mutations that perturb protein-protein interactions in the human 3D interactome, showing their association with cancer survival and drug response.