Qian Zhao

NexuST: A Hierarchical Foundation Model for Spatial Transcriptomics

NexuST is a hierarchical foundation model for spatial transcriptomics that improves cell-type annotation and spatial prediction by integrating gene-level and cell-level modeling.

metaAPA: a tool for integration of PolyA site predictions from single-cell and spatial transcriptomics

metaAPA integrates polyA site predictions from multiple tools to provide high-confidence and subset-supported sites for single-cell and spatial transcriptomics data.

CellPie: a scalable spatial transcriptomics factor discovery method via joint non-negative matrix factorization

CellPie is a fast, unsupervised method for factor discovery in spatial transcriptomics using joint non-negative matrix factorization, showing improved performance on human cancer datasets.

BioBatchNet: A Dual-Encoder Framework for Robust Batch Effect Correction in Imaging Mass Cytometry

BioBatchNet corrects batch effects in imaging mass cytometry data using a dual-encoder framework, outperforming existing methods and showing generalizability to scRNA-seq data.

Guidelines for alternative polyadenylation identification tools using single-cell and spatial transcriptomics data

The paper evaluates APA identification tools in single-cell and spatial transcriptomics, finding no single method is optimal, and recommends tool selection based on data characteristics.

TriTan: An efficient triple non-negative matrix factorisation method for integrative analysis of single-cell multiomics data

TriTan is a triple non-negative matrix factorisation method for single-cell multiomics data integration, offering efficient computation and improved interpretability.