Towards Cross-Sample Alignment for Multi-Modal Representation Learning in Spatial Transcriptomics
Justina Dai, Kalin Nonchev, Viktor Hendrik Koelzer, Gunnar Rätsch
This paper introduces a framework that aligns spatial transcriptomics data across multiple samples by integrating transcriptomics correction with deep learning, improving integration performance over existing methods.
bioRxiv · Mar 3, 2026 · PreprintBioinformatics