Spatial transcriptomics offers a revolutionary approach to understanding the tumor microenvironment (TME) in solid tumors by preserving the spatial context of gene expression, which is crucial for ...

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

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 ...

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 ...

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

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score ...

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 ...

The global spatial biology market is projected to grow at a compound annual growth rate (CAGR) of approximately 15% over the next five years. Key factors fueling this growth include the rising ...