Renyu Zhang

ATAT automates spatial transcriptomics analysis by aligning and traversing tissue samples using self-supervised learning, improving gene expression modeling without manual annotation.

This paper introduces a deep learning method for predicting protein contact maps, achieving higher accuracy than existing methods, especially for proteins with few sequence homologs.