Article

Path-MGCN: a pathway activity based multi-view graph convolutional network for determining spatial domains with attention mechanism

2024-05-29

Abstract excerpt

<title>Abstract</title> <p>Gene functional relationships are always ignored in spatial-domain recognition based on spatial transcriptomics (ST). We develop Path-MGCN, a multi-view graph convolutional network (MGCN) with attention mechanism that embeds pathway information. We generate a pathway activity profile with spot-specific pathway enrichment. Unique and shared embeddings from pathway and spatial graphs are...

Topics

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

Identifiers and source

Literature Corpus work: 52650696-807c-5505-9acc-89a1273828f1
DOI: 10.21203/rs.3.rs-4481813/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Path-MGCN: a pathway activity based multi-view graph convolutional network for determining spatial domains with attention mechanismDOI 10.21203/rs.3.rs-4481813/v1Read

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

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

Network-guided supervised learning on gene expression using a graph convolutional neural networkSemantic proximity Read

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

Multi-Level Attention Graph Neural Network for Clinically Interpretable Pathway-Level Biomarkers DiscoverySemantic proximity Read

Multi-omics data integration via novel interpretable k-hop graph attention network for signaling network inferenceSemantic proximity Read

Cancer subtype classification and modeling by pathway attention and propagationSemantic proximity Read

PGCNMDA: Learning node representations along paths with graph convolutional network for predicting miRNA-disease associations.Semantic proximity Read

STARNet enables spatially resolved inference of gene regulatory networks from spatial multi-omics dataSemantic proximity Read

MCNET: Multi-Omics Integration for Gene Regulatory Network Inference from scRNA-seqSemantic proximity Read

Novae: a graph-based foundation model for spatial transcriptomics dataSemantic proximity Read

HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations.Semantic proximity Read