Xiangjie Li

This paper introduces CarDEC, a deep learning model that simultaneously corrects batch effects, denoises, and clusters scRNA-seq data, outperforming existing methods in multiple evaluations.

This study shows that suppressing miR-199a-5p reduces ulcerative colitis by increasing XBP1 expression through endoplasmic reticulum stress.

This paper introduces SpaGCN, a graph convolutional network that identifies spatial domains and spatially variable genes by integrating gene expression, spatial location, and histology in spatial transcriptomics data.

ItClust improves clustering and cell type classification in scRNA-seq by using iterative transfer learning with neural networks, outperforming existing methods across diverse datasets.

This paper introduces DESC, a deep learning method for single-cell clustering that improves accuracy and removes batch effects.

The paper investigates ACE2 expression in maternal-fetal interface and fetal organs using single-cell transcriptomics but was withdrawn due to insufficient analysis of ACE2 and TMPRSS2.