Spatial transcriptomics extends single-cell RNA sequencing (scRNA-seq) by providing
spatial context for cell type identification and analysis. Imaging-based spatial technologies …

Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of
cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation …

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

The expression profiles and spatial distributions of RNAs regulate many cellular functions.
Image-based transcriptomic approaches provide powerful means to measure both …

Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but
does not capture their spatial distribution nor reveal local networks of intercellular …

Charting an organs' biological atlas requires us to spatially resolve the entire single-cell
transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and …

Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over
the past decade, particularly in developmental biology, cancer, immunology, and …

Spatial localization is a key determinant of cellular fate and behavior, but methods for
spatially resolved, transcriptome-wide gene expression profiling across complex tissues are …

Spatial transcriptomics (ST) technologies are rapidly becoming the extension of single-cell
RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single …

Single-cell RNA sequencing methods can profile the transcriptomes of single cells but
cannot preserve spatial information. Conversely, spatial transcriptomics assays can profile …