Jiyang Yu

The paper presents a cell type-resolved proteomic atlas of Alzheimer's disease mouse models, identifying thousands of cell-specific protein changes and highlighting astrocyte-microglia signaling.

HistoSweep improves tissue quality control in gigapixel images by removing artifacts and preserving biologically relevant structures, enhancing analysis accuracy in digital pathology and spatial omics.

The paper introduces SINBA, a computational framework that identifies synergistic, brain-penetrant drug combinations for high-risk medulloblastoma, validating several candidates in preclinical models.

This study shows SOX2 is not required for NUT carcinoma initiation or maintenance in mice, challenging its assumed oncogenic role and suggesting limited utility for SOX2-targeted therapies.

The paper shows TEAD1/2 have both YAP/TAZ-dependent and -independent roles in neural progenitor lineage progression, promoting progression by inhibiting Notch and cooperating with INSM1.

This study identifies uridine metabolism as a therapeutic target for chemo-resistant B-ALL by linking active signaling to uridine dependency and demonstrating DHODH inhibition as a promising treatment.

The paper identifies differences in mtDNA mutation accumulation and selective pressures in pediatric leukemias using bulk and single-cell sequencing, linking these to functional heterogeneity among leukemic cells.

This study identifies HKDC1 as a prometastatic enzyme in liver cancer that stabilizes β-catenin under hypoxia, enhancing cancer stemness.

This paper creates a spatial cell atlas of neuroblastoma, revealing tumor heterogeneity through multi-omics data and identifying spatial compartmentalization and signaling patterns.

scMINER identifies hidden drivers and network rewiring in single-cell RNA-seq data using mutual information, outperforming existing methods in clustering and network inference.

The paper identifies TCF4 and ID3 as key transcription factors driving mammary epithelial stem cell differentiation through single-cell RNA sequencing analysis.

The paper introduces a fast hashing method for comparing semi-structured data, demonstrating its use on electronic health records for duplicate detection and clustering.