Many biological functions and systems are influenced by how gene expression is spatially distributed, from subcellular through to tissue, organ, or at embryonic level. Our understanding of these ...

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.

Spatial transcriptomics (ST) emerges as a pivotal technique for cataloging gene expression across tissue sections while retaining crucial locational data. Traditional methodologies, encompassing bulk ...

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 ...

Illumina is raising the curtain on its upcoming entry into spatial transcriptomics, with tech designed to help researchers explore cellular behavior mapped across complex tissues. The announcement ...

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 ...

Explore how clinical multi-omics integration drives systems medicine, detailing data fusion methodologies and lab ...

Mapping biological networks in lung adenocarcinoma using transcriptomic analysis to identify prognostic biomarkers and therapeutic targets.

Comparison of dose-dense versus standard neoadjuvant chemotherapy for HER2 negative breast cancer: Retrospective, multicenter, real-world, Japanese study (JONIE5). MRI concentric partial response ...