The recent advancement in spatial transcriptomics technology has enabled multiplexed
profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the …

Spatial transcriptomics technologies developed in recent years can provide various
information including tissue heterogeneity, which is fundamental in biological and medical …

One major challenge in analyzing spatial transcriptomic datasets is to simultaneously
incorporate the cell transcriptome similarity and their spatial locations. Here, we introduce …

While technologies for multiplexed imaging have provided an unprecedented understanding
of tissue composition in health and disease, interpreting this data remains a significant …

The respiratory system's complex cellular heterogeneity presents unique challenges to
researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing …

Advances in transcriptomic technologies have deepened our understanding of the cellular
gene expression programs of multicellular organisms and provided a theoretical basis for …

Spatially resolved transcriptomics (SRT) has unlocked new dimensions in our
understanding of intricate tissue architectures. However, this rapidly expanding field …

Spatial gene expression in tissue is characterized by regions in which particular genes are
enriched or depleted. Frequently, these regions contain nested inside them subregions with …

The proper functioning of diverse biological systems depends on the spatial organization of
their cells, a critical factor for biological processes like shaping intricate tissue functions and …

Motivation Spatial clustering is essential and challenging for spatial transcriptomics' data
analysis to unravel tissue microenvironment and biological function. Graph neural networks …