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 ...

The spatial organization of cells is fundamental to multicellular life as it influences development, function and evolution. During development, the precise spatial arrangement of cells ensures proper ...

Single-cell RNA sequencing technologies profile the transcriptome of individual cells but lack the spatial context necessary for dissecting cellular interactions like cell-cell communications. On the ...

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 ...

Technological advances in sequencing have fueled the “omics revolution,” making big data a staple of biological research. However, many researchers feel ill-equipped to wrangle and analyze these ...

Why do so many promising drugs fail? This article explores how spatial multiomics reveals hidden cell interactions, helping ...

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 ...

High-throughput screening (HTS) and multi-omics technologies have each transformed drug discovery independently; their integration represents the next evolution in how laboratories move from compound ...

This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.