The idea that tumour microenvironment (TME) is organised in a spatial manner will not
surprise many cancer biologists; however, systematically capturing spatial architecture of …

Optimal integration of transcriptomics data and associated spatial information is essential
towards fully exploiting spatial transcriptomics to dissect tissue heterogeneity and map out …

With the rapid advancement in sequencing technologies, the concept of omics has
revolutionized our understanding of cellular behaviors. Conventional omics investigation …

Background Spatially-resolved transcriptomics has now enabled the quantification of high-
throughput and transcriptome-wide gene expression in intact tissue while also retaining the …

Spatial transcriptomics has been emerging as a powerful technique for resolving gene
expression profiles while retaining tissue spatial information. These spatially resolved …

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the
low-dimensional embeddings estimated in the dimension-reduction step may not be …

Spatially resolved transcriptomics (SRT) has evolved rapidly through various technologies,
enabling scientists to investigate both morphological contexts and gene expression profiling …

Spatially resolved transcriptomics is a relatively new technique that maps transcriptional
information within a tissue. Analysis of these datasets is challenging because gene …

Objectives Cholangiocarcinoma (CCA) is a heterogeneous malignancy with high mortality
and dismal prognosis, and an urgent clinical need for new therapies. Knowledge of the CCA …

Single-cell RNA-seq is a tool that generates a high resolution of transcriptional data that can
be used to understand regulatory networks in biological systems. In plants, several methods …