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We introduce a novel deep learning framework, SpaGene, which integrates scRNA-seq data and spatial transcriptomics data through an encoder-decoder architecture with translators, and discriminators, ...

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

The rapid development of spatial transcriptomics (ST) technologies has greatly advanced the understanding of gene expression, tissue architecture, cellular composition, and disease mechanisms within ...

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

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 ...

Abstract: Spatial transcriptomics technologies carry out advanced sequencing analysis of molecular profiles with a spatial context, providing multi-source information essential for elucidating ...

Spatial transcriptomics (ST) technologies reveal the spatial organization of gene expression in tissues, providing critical insights into development, neurobiology, and cancer. However, the high cost ...

Background: Lung tissue exhibits intricate spatial organization and dynamic cellular interactions. However, the molecular mechanisms underlying pulmonary arterial hypertension (PAH) remain poorly ...