Article

Deciphering shared and divergent tissue architectures from cross-species spatial transcriptomics

2026-06-18

Abstract excerpt

The integration of spatial transcriptomics (ST) data across species is essential for cross-species and translational studies, but remains challenging due to molecular divergence and anatomical differences between organisms. We present STACAME, a graph attention autoencoder-based framework to decipher shared and divergent tissue architectures from cross-species ST data by explicitly modeling both orthologous and sp...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 881e5c45-f3cc-52f9-b9a0-f7a4daad383d
DOI: 10.64898/2026.06.16.732760

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deciphering shared and divergent tissue architectures from cross-species spatial transcriptomicsDOI 10.64898/2026.06.16.732760Read

Integrating spatial transcriptomics data across different conditions, technologies, and developmental stagesSemantic proximity Read

BrainBeacon: A Cross-Species Foundation Model for Single-cell Resolved Brain Spatial TranscriptomicsSemantic proximity Read

Cross-view graph neural networks for spatial domain identification by integrating gene expression, spatial locations with histological imagesSemantic proximity Read

Enhancement of network architecture alignment in comparative single-cell studiesSemantic proximity Read

Enhancement of Network Architecture Alignment in Comparative Single-Cell StudiesSemantic proximity Read

Geometric inference of cross-species transcriptome correspondence using Gromov-Wasserstein optimal transportSemantic proximity Read

INSPIRE: interpretable, flexible and spatially-aware integration of multiple spatial transcriptomics datasets from diverse sourcesSemantic proximity Read

Integrative cross-sample alignment and spatially differential gene analysis for spatial transcriptomicsSemantic proximity Read

JADE: Joint Alignment and Deep Embedding for Multi-Slice Spatial TranscriptomicsSemantic proximity Read

Translating Brain Anatomy and Disease from Mouse to Human in Latent Gene Expression SpaceSemantic proximity Read

Brain and Organoid Manifold Alignment (BOMA), a machine learning framework for comparative gene expression analysis across brains and organoidsSemantic proximity Read

OT-knn: a neighborhood-aware optimal transport framework for aligning spatial transcriptomics dataSemantic proximity Read