Yunfei Hu

The paper introduces SpaMV, a method for integrating spatial multi-omics data that preserves modality-specific information and improves clustering and dimensionality reduction.

MaskGraphene integrates multi-slice, multi-condition spatial transcriptomics data using a graph neural network to generate interpretable joint embeddings with preserved geometric information, improving downstream analyses.

AquilaDeepFilter improves the precision of large deletion SV detection from linked-reads by using a deep learning ensemble, while maintaining high recall and outperforming existing methods.

The paper develops a text mining pipeline to extract gene-phenotype associations from autism-related literature, creating a database that can aid in understanding autism mechanisms and treatment.