Motivation The rapid development of spatial transcriptome technologies has enabled
researchers to acquire single-cell-level spatial data at an affordable price. However …

Motivation Single-cell RNA sequencing (scRNA-seq) techniques have revolutionized the
investigation of transcriptomic landscape in individual cells. Recent advancements in spatial …

Abstract Single-Cell RNA sequencing (scRNA-seq) has provided unprecedented
opportunities for exploring gene expression and thus uncovering regulatory relationships …

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

Integrative analysis of single-cell RNA-sequencing (scRNA-seq) data with spatial data for
the same species and organ would provide each cell sample with a predictive spatial …

Single-cell technologies are emerging fast due to their ability to unravel the heterogeneity of
biological systems. While scRNA-seq is a powerful tool that measures whole-transcriptome …

In the analysis of both single-cell RNA sequencing (scRNA-seq) and spatially resolved
transcriptomics (SRT) data, classifying cells/spots into cell/domain types is an essential …

Accurate mapping between single‐cell RNA sequencing (scRNA‐seq) and low‐resolution
spatial transcriptomics (ST) data compensates for both limited resolution of ST data and …

Since many single-cell RNA-seq (scRNA-seq) data are obtained after cell sorting, such as
when investigating immune cells, tracking cellular landscape by integrating single-cell data …

Most sequencing-based spatial transcriptomics (ST) technologies do not achieve single-cell
resolution where each captured location (spot) may contain a mixture of cells from …