A team of Vanderbilt researchers has released a new benchmarking study that aims to assist scientists in selecting the most effective methods for analyzing spatial transcriptomics (ST) data. ST ...

In a recent study published in Nature Communications, a team of researchers at the Carl R. Woese Institute for Genomic Biology reports a new, robust computational toolset to extract biological ...

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 ...

The rapid development of spatial transcriptomics (ST) technologies has greatly advanced the understanding of gene expression, tissue architecture, cellular composition, and disease mechanisms within ...

Biological systems are inherently three-dimensional—tissues form intricate layers, networks, and architectures where cells interact in ways that extend far beyond a flat plane. To capture the true ...

Spatial transcriptomics data from osteosarcoma cells. Left) A spatial map of the transcriptome segmented into individual cells using machine learning, with each dot representing a RNA transcript and ...

Gene expression profiling using bulk and single-cell transcriptomic techniques has transformed our understanding of osteoarthritis (OA) by depicting the dynamic molecular changes in cartilage, ...