Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods,
together with associated computational tools and the growing availability of public data …

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their
success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics …

Major depressive disorder (MDD) is a common, heterogenous, and potentially serious
psychiatric illness. Diverse brain cell types have been implicated in MDD etiology …

Transcriptome level expression data connected to the spatial organization of the cells and
molecules would allow a comprehensive understanding of how gene expression is …

An essential task in spatial transcriptomics is identifying spatially variable genes (SVGs).
Here, we present Celina, a statistical method for systematically detecting cell type-specific …

Spatial transcriptomic technologies enable measurement of expression levels of genes
systematically throughout tissue space, deepening our understanding of cellular …

The recent arrival of high-resolution spatial transcriptomics (ST) technologies is generating a
veritable revolution in life sciences, enabling biomolecules to be measured in their native …

The mechanisms of cardiovascular diseases (CVDs) remain incompletely elucidated. Single-
cell RNA sequencing (scRNA-seq) has enabled the profiling of single-cell transcriptomes at …

Identifying spatially variable genes (SVGs) is a key step in the analysis of spatially resolved
transcriptomics data. SVGs provide biological insights by defining transcriptomic differences …

Spatially resolved transcriptomics has been dramatically transforming biological and
medical research in various fields. It enables transcriptome profiling at single‐cell, multi …