Wenwen Min

SpaBatch aligns spatial transcriptomics data across batches using graph deep learning to reduce technical variability and enable multi-slice integration.

This paper introduces scstGCN, a method that fuses histology, spatial transcriptomics, and spatial location data to infer single-cell resolution gene expression from spot-based spatial transcriptomics data.

The paper introduces STMask, a graph self-supervised learning method for spatial transcriptomics data, improving spatial clustering and trajectory inference.

This study uses a crowdsourcing approach to stratify ALS patients, identifying four distinct clusters with unique predictors and improving outcome prediction.