The study of immunology, traditionally reliant on proteomics to evaluate individual immune
cells, has been revolutionized by single-cell RNA sequencing. Computational …

Spatially resolved gene expression profiling provides insight into tissue organization and
cell–cell crosstalk; however, sequencing-based spatial transcriptomics (ST) lacks single-cell …

Spatial transcriptomics, leveraging sequencing-and imaging-based techniques, has
emerged as a groundbreaking technology for mapping gene expression within the complex …

Spatial omics technologies can help identify spatially organized biological processes, but
existing computational approaches often overlook structural dependencies in the data. Here …

Efficiently mapping of cell types in situ remains a major challenge in spatial transcriptomics.
Most spot deconvolution tools ignore spatial coordinate information and perform extremely …

Interactions between tumor cells and immune cells in the tumor microenvironment (TME)
play a vital role the mechanisms of immune evasion, by which cancer cells escape immune …

Spatially resolved transcriptomics has revolutionized genome-scale transcriptomic profiling
by providing high-resolution characterization of transcriptional patterns. Here, we present …

With the application of spatial biology, the detection and identification of the diverse cell
types present in the tumor microenvironment, including specific immune subsets, is possible …

In the era of single-cell genomics, deciphering cellular heterogeneity is paramount for
understanding complex biological systems. Providing correct cell type annotations is a …

Recent spatial omics research leverages the assumption that spatial information enhances
model performance on the cell type annotation task. This study investigates and challenges …