Hang Xu

PMAIP1-Mediated Glucose Metabolism and its Impact on the Tumor Microenvironment in Breast Cancer: Integration of Multi-Omics Analysis and Experimental Validation

This study identifies prognostic genes related to glucose metabolism in breast cancer and develops a model linking metabolism and immune infiltration, validated through experiments and single-cell analysis.

Integrated analysis of spatial multi-omics with SpatialGlue

SpatialGlue integrates spatial multi-omics data using a graph neural network to improve spatial domain detection and cross-modality correlation analysis.

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

GraphST improves spatial transcriptomics analysis by integrating clustering, integration, and deconvolution through graph self-supervised contrastive learning, achieving higher accuracy than existing methods.

Unsupervised Spatial Embedded Deep Representation of Spatial Transcriptomics

SEDR couples a deep autoencoder over expression with a variational graph autoencoder over position, improving clustering in dorsolateral prefrontal cortex and splitting a visually uniform breast tumour region.

Whole genome base-wise aggregation and functional prediction for human non-coding regulatory variants

This paper develops regBase, a database of whole genome base-wise aggregations of regulatory variant predictions, and three composite models to score functional, pathogenic, and cancer driver variants, showing superior performance in fine-mapping causal variants.