Spatial transcriptomics and gene expression analysis represent a transformative approach in biomedical research, integrating the spatial context of tissues with high-resolution profiling of gene ...

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 ...

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 ...

A new spatial transcriptomic technology captures RNA patterns without requiring expensive imaging ...

A collaborative project has created a comprehensive guide to help standardize spatial transcriptomics practices. Spatial transcriptomics provides a unique perspective on the genes that cells express ...

The global spatial biology market is projected to grow at a compound annual growth rate (CAGR) of approximately 15% over the ...

The integration of single-cell and spatial transcriptomics with advanced metabolic profiling tools has revolutionized the ...

Spatial transcriptomics is a technique that provides information about gene expression patterns within intact tissues. This technology employs various methodologies, including in situ sequencing (ISS) ...

A new software tool, ovrlpy, improves quality control in spatial transcriptomics, a key technology in biomedical research. Developed by the Berlin Institute of Health at Charité (BIH) in international ...