Advances in spatial omics technologies have improved the understanding of cellular
organization in tissues, leading to the generation of complex and heterogeneous data and …

Recent technological developments in spatial transcriptomics allow researchers to measure
gene expression of cells and their spatial locations at the single-cell level, generating …

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

Spatially resolved omics technologies are transforming our understanding of biological
tissues. However, the handling of uni-and multimodal spatial omics datasets remains a …

Spatial clustering, which shares an analogy with single-cell clustering, has expanded the
scope of tissue physiology studies from cell-centroid to structure-centroid with spatially …

Tissue structure identification is a crucial task in spatial omics data analysis, for which
increasingly complex models, such as Graph Neural Networks and Bayesian networks, are …

Rapid advances in spatial transcriptomics (ST) have revolutionized the interrogation of
spatial heterogeneity and increase the demand for comprehensive methods to effectively …

Single-cell RNA sequencing (scRNA-seq) provides insights into gene expression
heterogeneities in diverse cell types underlying homeostasis, development and pathological …

Communications between tumor cells and surrounding immune cells help shape the tumor
immunity continuum. Recent breakthroughs in high-throughput technologies as well as …

Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell
heterogeneity and develop new immunotherapy strategies for cancer research. There is an …