Yi Chen Zhao

NicheTrans translates single-omics data into spatial multi-omics insights by integrating spatial and multi-modal information, outperforming existing methods in disease and tissue analysis.

This study uses single-cell multi-omics to analyze immune reconstitution failure in HIV patients, identifying genetic and epigenetic factors and developing a predictive model.

The paper introduces CIMA, a multi-omics atlas of human immune cells, identifying regulatory mechanisms and genetic associations across sex, age, and genetic factors.

SpatialZ generates dense 3D cell atlases from planar spatial transcriptomics data by reconstructing virtual slices, validated with real 3D data and enabling new spatial analyses.

This study identifies circAβ-a RNA as a driver of Aβ175 oligomer formation and plaque deposition in sporadic Alzheimer's disease using mouse models and human brain samples.

This study introduces BINARY, a graph convolutional network using binarized spatial transcriptomics data to identify spatial domains, outperforming existing methods with less input.

YiNet integrates TCM and Western medicine data to study viral infectious diseases, providing tools for pharmacological analysis and drug development.

This paper introduces scFAST-seq, a high-throughput single-cell full-length RNA sequencing method that improves detection of non-polyadenylated transcripts and RNA velocity, and enables simultaneous mutation and cellular status identification in tumor cells.

The paper identifies lncRNAs in human germ cells and shows LNC1845 regulates LHX8 through histone modifications during gonadal development.

The paper uses spatial transcriptome analysis in a mouse model of intraventricular haemorrhage to identify 3D gene expression trajectories and neural circuits involved in secondary brain injury.

dbDEMC 3.0 updates a database of differentially expressed miRNAs in human and model organism cancers, expanding data entries and integrating functional annotations.

The paper provides a comprehensive catalog of lncRNAs in human T cells across three cancer types, identifies 154 signature lncRNAs associated with T cell states, and highlights their potential roles in cancer immunity.