Andrei Smolnikov

This study uses deep learning to compare human and mouse gene expression across 777K bulk RNA-seq samples, identifying genes with differing functional associations between species.

The paper develops GeneRAIN models trained on bulk RNA-seq data to predict gene attributes, showing they capture biological information beyond gene expression and outperform existing models.

This study identifies three lncRNAs consistently dysregulated across eight cancer types and shows they are involved in similar biological processes related to cancer progression.