Spatial transcriptomics data analysis increasingly depends on artificial intelligence (AI) to convert raw, location-tagged gene expression readings into a usable map of tissue biology. Unlike ...

Spatial biology is rapidly becoming an essential tool for understanding complex biological systems, but realizing its full potential requires more than access to technology. Researchers need ...

Researchers have developed REBOSEP, a computational workflow that maps gene expression as a continuous signal across tissue ...

A new computational framework called CellART unifies cell segmentation and cell-type annotation across high-resolution ...

Biological tissues are made up of different cell types arranged in specific patterns, which are essential to their proper functioning. Understanding these spatial arrangements is important when ...

Spatial transcriptomics is a cutting-edge technique that characterizes gene expression within sections of tissue, such as heart, skin or liver tissue. These snapshots provide insights into how spatial ...

Biological tissues are made up of different cell types arranged in specific patterns, which are essential to their proper functioning. Understanding these spatial arrangements is important when ...

Spatial transcriptomics provides a unique perspective on the genes that cells express and where those cells are located. However, the rapid growth of the technology has come at the cost of ...

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics are providing increasingly detailed views of complex cellular ecosystems, enabling researchers to investigate cellular heterogeneity, ...

Newswise — Spatial transcriptomics is a cutting-edge technique that characterizes gene expression within sections of tissue, such as heart, skin or liver tissue. These snapshots provide insights into ...