The ability to localize hundreds of macromolecules to discrete locations, structures and cell
types in a tissue is a powerful approach to understand the cellular and spatial organization …

Bioinformatic analysis of large and complex omics datasets has become increasingly useful
in modern day biology by providing a great depth of information, with its application to …

Single cell RNA-sequencing (scRNA-seq) advancements have helped detect transcriptional
heterogeneities in biological samples. However, scRNA-seq cannot currently provide high …

Background: The first spatially resolved transcriptomics platforms, GeoMx (Nanostring) and
Visium (10x Genomics) were launched in 2019 and were recognized as the method of the …

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 …

Profiling spatial variations of cellular composition and transcriptomic characteristics is
important for understanding the physiology and pathology of tissues. Spatial transcriptomics …

Cells of multicellular plants possess inherent heterogeneity. Recent progress in single-cell
RNA sequencing (scRNA-seq) allows researchers to classify, characterize, and distinguish …

Abstract Characterization of cell heterogeneity in gene expression is a “hot” but complex
issue in the fields of biology and medicine. Therefore, high-resolution RNA sequencing …

Deciphering the features, structure, and functions of the cell niche in tissues remains a major
challenge. Here, we present scNiche, a computational framework to identify and …

A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the
computational methods. A widely-used approach involves utilizing simulated data. However …