Yang Liu

This study identifies prognostic gene markers in recurrent IDH wild-type gliomas using network-based analysis and survival modeling, revealing genes associated with survival outcomes and recurrence patterns.

The paper introduces EGNF, a graph-based framework for biomarker discovery that outperforms traditional methods in classification accuracy and interpretability across cancer datasets.

This paper identifies YX0798 as a potent, selective, and orally effective CDK9 inhibitor that overcomes therapeutic resistance in lymphoma by inducing transcription reprogramming and cell death.

This paper develops network-regularized AFT models with inverse-degree penalties for survival analysis in cancer genomics, showing improved biological interpretability and reduced false positives.

This paper optimizes saRNA platforms for enhanced protein expression and organ-specific targeting, identifying three alphavirus-derived constructs with improved performance in vivo.

This paper introduces SpaGFT, a graph Fourier transform model for spatial omics data analysis, enabling accurate identification of tissue modules and their functional relationships in spatial transcriptomics and proteomics data.

The paper identifies reduced KCNQ2/3 expression and impaired spike frequency adaptation in TLE patients and mouse models, showing their role in promoting seizure activity.

The paper identifies early gut biomarkers for Parkinson's disease in mice and humans using a transgenic model and molecular profiling.