Tao Wang

This study shows that Prnd/Doppel in endothelial cells promotes vascular remodeling and long-term recovery after stroke, improving neuronal survival and reducing inflammation.

This study identifies FXR2 as a mediator of autophagy that clears Sindbis virus capsid and protects against viral encephalitis by reducing viral protein toxicity.

This paper develops a novel CAR-M targeting GPC3 with IFN-gamma and SIRPECD to enhance anti-tumor activity in hepatocellular carcinoma.

This study introduces a deep learning model called spacer to analyze spatially resolved transcriptomics data, revealing novel insights into cellular recruitment mechanisms in tumors and heart tissue during myocarditis.

This study shows that liver cancer initiation depends on metabolic zonation but is not linked to premalignant clonal expansion.

This study investigates the role of GlialCAM's cytoplasmic tail in white matter homeostasis using a mutant mouse model, revealing defects in ECM remodeling and glial activation.

The paper introduces a Bayesian framework to map cell-cell interactions from spatial transcriptomics data, revealing new biological insights in cancer and immune responses.

This study shows ZNF397 loss leads to TET2-driven epigenetic changes, lineage plasticity, and resistance to AR-targeted therapies in AR-dependent cancers, with TET2 inhibitors reversing resistance.

This paper develops pMTnet-omni, an AI system predicting TCR-pMHC binding across species and MHC classes, achieving high accuracy and showing clinical utility in predicting immune-related adverse events.

This study shows that IGFBP2-expressing midlobular hepatocytes contribute to liver homeostasis and regeneration after injury or fasting.

This paper benchmarks 21 dimension reduction methods on CyTOF data, finding SAUCIE, SQuaD-MDS, and scvis as top performers with different strengths.

This study shows that Arid1a loss enhances pancreatic β-cell regeneration by activating EGF signaling, protecting against diabetes.

The paper introduces a deep-learning method called TPS to quantify zonal gene expression patterns in tissues like the liver, showing it can detect differences between strains, ages, and disease states.

The paper introduces the CSiN score to predict immunotherapy outcomes by assessing tumor neoantigen quality through clonality and immunogenicity, showing improved performance over existing methods.

SCINA is a semi-supervised model for analyzing scRNA-Seq and flow cytometry data, improving accuracy and efficiency over unsupervised methods by leveraging gene signatures.

RISC integrates scRNA-seq datasets with overlapping cell clusters using PCR, improving accuracy in datasets with similar cell types but distinct functional states.

This paper presents a crowdsourced challenge to predict early discontinuation of docetaxel in mCRPC patients using clinical data from multiple trials, finding that ensemble models outperform individual models.