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 ...

Single-cell transcriptomics has revolutionized the study of cellular diversity and function by enabling gene expression analysis at single-cell resolution. The technique is crucial for understanding ...

The global transcriptome sequencing market is projected to reach $11.8 billion by 2035, growing at a 7.3% CAGR from 2025 to 2035. Growth is driven by falling sequencing costs, precision medicine, drug ...

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.

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 ...

A new spatial transcriptomics framework compares tumor “floor plans,” revealing conserved spatial groups that may relate ...

Researchers reveal the intricate molecular landscape of triple-negative breast cancer (TNBC), uncovering actionable spatial archetypes and gene signatures that pave the way for personalized therapies ...

The field of spatial transcriptomics utilizes technologies that map gene expression data to specific cellular locations within tissues. While traditional RNA sequencing methods generate quantitative ...

Researchers at the Max Delbrück Center have developed an open-source spatial transcriptomics (ST) platform, called Open-ST, that creates 3D molecular maps from patient tissue samples with subcellular ...

Spatial transcriptomics now spans two fundamentally different measurement strategies, and the choice between them shapes every downstream result a lab will generate. Sequencing-based platforms capture ...