Atishay Jain

DRIFT improves spatial transcriptomics analysis by integrating spatial context into foundation models using diffusion on spatial graphs, outperforming specialized methods.

STING improves spatial transcriptomics clustering by integrating gene-gene and spatial relations through nested graph neural networks, achieving better clustering performance across multiple datasets.

This paper evaluates deep-learning methods for improving Hi-C resolution using experimentally generated datasets and finds they perform poorly on sparse data, with retraining offering limited improvement.