Cell atlasing efforts rest on a deceptively simple premise: To understand a tissue, you must find every cell in it, including the rare populations and transitional states whose biology is often the ...

A novel spatial transcriptomics atlas developed by Northwestern Medicine scientists may improve the understanding of niche cellular interactions in the gastrointestinal tract that promote the ...

This study addresses a critical challenge in spatial multi-omics: the effective integration of heterogeneous molecular modalities within complex tissue environments. By introducing SpaDDM, a ...

Abstract: Spatial transcriptomics has revolutionized the ability to investigate transcriptional patterns within tissue morphology. However, many ST clustering pipelines operate on a single preselected ...

Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...

The tumor microenvironment (TME) of invasive lobular carcinoma (ILC) remains largely unexplored despite its clinical relevance and distinct biology. Using spatial transcriptomics, we reveal insights ...

Foster City, Calif. | January 27, 2026 — Signios Bio today announced the launch of a new grant program supporting innovative spatial transcriptomics research using the 10x Genomics Xenium 5K Spatial ...

Artificial intelligence (AI) has become a common tool for bioinformatics, with hundreds of methods published in recent years. Due to the training data demands of deep-learning algorithms, ...

Spatial ribonucleic acid (RNA) transcriptomics measures gene expression while preserving each molecule’s coordinates in intact tissue, tying transcripts to histology and local microenvironments.