Article

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

2024-07-26

Abstract excerpt

The latest developments in spatial transcriptomics technology provide an unprecedented opportunity for in situ elucidation of tissue structure and function. Spatial transcriptomics can provide simultaneous, multi-modal, and complementary information, including gene expression profiles, spatial positions, and histological images. Despite these capabilities, current methodologies often fall short in fully integratin...

Topics

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

Identifiers and source

Literature Corpus work: ae7e1f7d-f59d-5712-bd77-4579aca6fe34
DOI: 10.1101/2024.07.25.605067

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Cross-view graph neural networks for spatial domain identification by integrating gene expression, spatial locations with histological imagesDOI 10.1101/2024.07.25.605067Read

Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learningSemantic proximity Read

Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learningSemantic proximity Read

stGCL: A versatile cross-modality fusion method based on multi-modal graph contrastive learning for spatial transcriptomicsSemantic proximity Read

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

BertST: BERT-based Spatial Domain Identification in Patient DataSemantic proximity Read

HarveST: Heterogeneous Graph Learning Framework for Revealing Spatial Transcriptomics PatternsSemantic proximity Read

SEDIST: Spatially Enhanced Domain Identification through Spatial TranscriptomicsSemantic proximity Read

Unsupervised Spatially Embedded Deep Representation of Spatial TranscriptomicsSemantic proximity Read

stGRL: spatial domain identification, denoising, and imputation algorithm for spatial transcriptome data based on multi-task graph contrastive representation learningSemantic proximity Read

PathCLAST: Pathway-Augmented Contrastive Learning with Attention for Spatial TranscriptomicsSemantic proximity Read

Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location and histology using GCNSemantic proximity Read